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![2 ◾ Libo Song and David F. Kotz
© 2011 by Taylor & Francis Group, LLC
1.1 Routing in Mobile Opportunistic Networks*
Routing in mobile ad hoc networks has been studied extensively. Most of these
studies assume that a contemporaneous end-to-end path exists for the network
nodes. Some mobile ad hoc networks, however, may not satisfy this assumption.
In mobile sensor networks [26], sensor nodes may turn off to preserve power. In
wild-animal tracking networks [13], animals may roam far away from each other.
Other networks, such as pocket-switched networks [9], battlefield networks [7,18],
and transportation networks [1,16], may experience similar disconnections due to
mobility, node failure, or power-saving efforts.
One solution for message delivery in such networks is that the source passively
waits for the destination to be in communication range and then delivers the mes-
sage. Another active solution is to flood the message to any nodes in communica-
tion range. The receiving nodes carry the message and repeatedly flood the network
with the message. Both solutions have obvious advantages and disadvantages: the
first may have a low delivery ratio while using few resources; the second may have
a high delivery ratio while using many resources.
Many other opportunistic routing protocols have been proposed in the litera-
ture. Few of them, however, were evaluated in realistic network settings, or even in
realistic simulations, due to the lack of any realistic people mobility model. Random
walk or random way-point mobility models are often used to evaluate the perfor-
mance of those routing protocols. Although these synthetic mobility models have
received extensive interest from mobile ad hoc network researchers [2], they do not
reflect people’s mobility patterns [10]. Realizing the limitations of using random
mobility models in simulations, a few researchers have studied routing protocols in
mobile opportunistic networks with realistic mobility traces. In the Haggle project,
Chaintreau et al. [3] theoretically analyzed the impact of routing algorithms over
a model derived from a realistic mobility data set. Su et al. [23] simulated a set of
routing protocols in a small experimental network. Those studies help researchers
better understand the theoretical limits of opportunistic networks and the routing
protocol performance in a small network (20–30 nodes).
Deploying and experimenting with large-scale mobile opportunistic networks
is difficult, so we also resort to simulation. Instead of using a complex mobility
* This work is based on an earlier work: “Evaluating Opportunistic Routing Protocols with
Large Realistic Contact Traces,” in Proceedings of the Second ACM Workshop on Challenged
Networks, ©ACM 2007. http://doi.acm.org/10.1145/1287791.1287799.
1.1.4.4 Metrics..............................................................................10
1.1.4.5 Results...............................................................................11
1.1.5 Related Work...................................................................................18
1.1.6 Summary.........................................................................................21
References............................................................................................................22](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-19-2048.jpg)
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© 2011 by Taylor & Francis Group, LLC
model to mimic people’s mobility patterns, we used mobility traces collected in a
production wireless network at Dartmouth College to drive our simulation. Our
message-generation model, however, was synthetic.
We study protocols for routing messages between wireless networking devices car-
ried by people. We assume that people send messages to other people occasionally, using
their devices; when no direct link exists between the source and the destination of the
message, other nodes may relay the message to the destination. Each device represents a
unique person (it is out of the scope of our work to cover instances when a device may
be carried by different people at different times). Each message is destined for a specific
person and thus for a specific node carried by that person. Although one person may
carry multiple devices, we assume that the sender knows which device is the best to
receive the message. We do not consider multicast or geocast in this chapter.
Using realistic contact traces, which we derived from the Dartmouth College data-
set [15], we evaluated the performance of three “naive” routing protocols (direct-deliv-
ery, epidemic, and random) and two prediction-based routing protocols, PRoPHET
[19] and Link-State [23]. We also propose a new prediction-based routing protocol and
compare it to the above protocols.
1.1.1 Routing Protocol
A routing protocol is designed for forwarding messages from one node (source) to
another node (destination). Any node may generate messages for any other node
and may carry messages destined for other nodes. We consider only messages that
are unicast (single destination).
Delay-tolerant networks (DTN) routing protocols can be described in part by their
transfer probability and replication probability; that is, when one node meets another
node, what is the probability that a message should be transferred and, if so, whether the
sender should retain its copy. Two extremes are the direct-delivery protocol and the epi-
demic protocol. The former transfers with probability 1 when the node meets the desti-
nation, 0 for others, and never replicates a packet; in effect, the packet only moves when
the source meets the destination. The latter uses transfer probability 1 for all nodes and
replicates the packet each time it meets another node. Both these protocols have their
advantages and disadvantages. All other protocols are between the two extremes.
First, we define the notion of contact between two nodes. Then we describe five
existing protocols before presenting our own proposal.
A contact is defined as a period of time during which two nodes have the oppor-
tunity to communicate. Although wireless technologies differ, we assume that a
node can reliably detect the beginning and end time of a contact with nearby nodes.
A node may be in contact with several other nodes at the same time.
The contact history of a node is a sequence of contacts with other nodes. Node
i has a contact history Hij, for each other node j, which denotes the historical con-
tacts between node i and node j. We record the start and end time for each contact;
however, the last contacts in the node’s contact history may not have ended.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-20-2048.jpg)
![4 ◾ Libo Song and David F. Kotz
© 2011 by Taylor & Francis Group, LLC
1.1.1.1 Direct Delivery Protocol
In this simple protocol, a message is transmitted only when the source node can
directly communicate with the destination node of the message. In mobile oppor-
tunistic networks, however, the probability for the sender to meet the destination
may be low, or even zero.
1.1.1.2 Epidemic Routing Protocol
The epidemic routing protocol [24] floods messages into the network. The source
node sends a copy of the message to every node that it meets. The nodes that receive
a copy of the message also send a copy of the message to every node that they meet.
Eventually, a copy of the message arrives at the destination of the message.
This protocol is simple but may use significant resources; excessive communication
may drain each node’s battery quickly. Moreover, since each node keeps a copy of each
message, storage is not used efficiently and the capacity of the network is limited.
At a minimum, each node must expire messages after some amount of time or
stop forwarding them after a certain number of hops. After a message expires, the
message will not be transmitted and will be deleted from the storage of any node
that holds the message.
An optimization to reduce the communication cost is to transfer index messages
before transferring any data message. The index messages contain IDs of messages
that a node currently holds. Thus, by examining the index messages, a node only
transfers messages that are not yet contained on the other nodes.
1.1.1.3 Random Routing
An obvious approach between the two extremes previously discussed is to select a
transfer probability between 0 and 1 to forward messages at each contact. The repli-
cation factor can also be a probability between 0 (none) and 1 (all). For our random
protocol, we use a simple replication strategy that makes no replicas. The message
is transferred every time the transfer probability is greater than the threshold. The
message has some chance of being transferred to a highly mobile node and thus
may have a better chance to reach its destination before the message expires.
1.1.1.4 PRoPHET Protocol
PRoPHET [19] is the Probabilistic Routing Protocol using History of past
Encounters and Transitivity, which is used to estimate each node’s delivery prob-
ability for each other node. When node i meets node j, the delivery probability of
node i for j is updated by
ij ij ij
p p p p
ʹ = − +
( )
1 ,
0 (1.1)](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-21-2048.jpg)
![Routing in Mobile Opportunistic Networks ◾ 5
© 2011 by Taylor & Francis Group, LLC
where p0 is an initial probability, a design parameter for a given network. Lindgren
et al. [19] chose 0.75, as did we in our evaluation. When node i does not meet j for
some time, the delivery probability decreases by
ʹ =
p p
ij
k
ij
α , (1.2)
where α is the aging factor (α < 1), and k is the number of time units since the last
update.
The PRoPHET protocol exchanges index messages as well as delivery probabili-
ties. When node i receives node j’s delivery probabilities, node i may compute the
transitive delivery probability through j to z with
ʹ = + −
p p p p p
iz iz iz ij jz
( )
1 β, (1.3)
where β is a design parameter for the impact of transitivity; we use β = 0.25 (as in
[19]).
ZebraNet [13] used a simple history-based routing protocol, which calculates the
probabilitysimilartoEquation(1.2)toestimatetheprobabilitythatanodecancommu-
nicate with the destination, the base station. Only one base station exists in ZebraNet.
1.1.1.5 Link-State Protocol
Su et al. [23] use a link-state approach to estimate the weight of each path from the
source of a message to the destination. They use the median intercontact duration
or exponentially aged intercontact duration as the weight on links. The exponen-
tially aged intercontact duration of node i and j is computed by
ʹ = + − −
w w t t
ij ij ij
α α
( )( )
1 , (1.4)
where t is the current time, tij is the time of last contact, and α is the aging factor.
At the first contact, we just record the contact time.
Nodes share their link-state weights when they can communicate with each
other, and messages are forwarded to the neighbor that has the path to destination
with the lowest link-state weight.
1.1.2 Timely Contact Probability
We, too, use historical contact information to estimate the probability of meeting
other nodes in the future. But our method differs in that we estimate the contact
probability within a period of time. For example, what is the contact probability in
the next hour? Neither PRoPHET nor Link-State considers time in this way.
One way to estimate the timely contact probability is to use the ratio of the
total contact duration to the total time. However, this approach does not capture
the frequency of contacts. For example, one node may have a long contact with](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-22-2048.jpg)
![8 ◾ Libo Song and David F. Kotz
© 2011 by Taylor & Francis Group, LLC
pij
(m) for any 0 < m < k, is above a threshold, or if j is the destination of the message,
node i will send a copy of the message to node j.
All the previous effort serves to determine the transfer probability when two
nodes meet. The replication decision is orthogonal to the transfer decision. In our
implementation, we always replicate. Although PRoPHET [19] and Link-State [23]
do no replication, as described, we added replication to both protocols for better
comparison to our protocol.
1.1.4 Evaluation Results
We evaluate and compare the results of direct delivery, epidemic, random,
PRoPHET, Link-State, and timely contact routing protocols.
1.1.4.1 Mobility Traces
We use real mobility data collected at Dartmouth College. Dartmouth College
has collected association and disassociation messages from devices on its wire-
less network since spring 2001 [15]. Each message records the wireless card
MAC address, the time of association and disassociation, and the name of the
access point (AP). We treat each unique MAC address as a node. For more
information about Dartmouth’s network and the data collection, see previous
studies [8,14].
Our data are not contacts in a mobile ad hoc network. We can approximate
contact traces by assuming that two users can communicate with each other when-
ever they are associated with the same access point. Chaintreau et al. [3] used
Dartmouth data traces and made the same assumption to theoretically analyze the
impact of human mobility on opportunistic forwarding algorithms. This assump-
tion may not be accurate,* but it is a good first approximation. In our simulation,
we imagine the same clients and same mobility in a network with no access points.
Since our campus has full Wi-Fi coverage, we assume that the location of access
points had little impact on users’ mobility.
We simulated one full month of trace data (November 2003), with 5,142 users.
Although prediction-based protocols require prior contact history to estimate each
node’s delivery probability, our preliminary results show that the performance
improvement of warming-up over one month of trace was marginal. Therefore, for
simplicity, we show the results of all protocols without warm-up.
* Two nodes may not have been able to directly communicate while they were at far sides of an
access point, or two nodes may have been able to directly communicate if they were between
two adjacent access points.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-25-2048.jpg)
![Routing in Mobile Opportunistic Networks ◾ 9
© 2011 by Taylor & Francis Group, LLC
1.1.4.2 Simulator
We developed a custom simulator.* Since we used contact traces derived from
real mobility data, we did not need a mobility model and omitted physical and
link-layer details for node discovery. We are aware that the time for neighbor
discovery in different wireless technologies varies from less than one second to
several seconds. Furthermore, connection establishment also takes time, such as
Dynamic Host Configuration Protocol (DHCP). In our simulation, we assumed
that the nodes could discover and connect to each other instantly when they were
associated with the same AP. To accurately model communication costs, how-
ever, we simulated some MAC-layer behaviors, such as collision.
The default settings of the network of our simulator are listed in Table 1.1,
using the values recommended by other papers [23,19]. The message probability
was the probability of generating messages, as described below in Section 1.1.4.3.
The default transmission bandwidth was 11 Mb/s. When one node tried to transmit
a message, it first checked whether another node was transmitting. If it was, the
node backed off for a random number of slots. Each slot was 1 millisecond, and
the maximum number of back-off slots was 30. The size of messages was uniformly
distributed between 80 bytes and 1024 bytes. The hop count limit (HCL) was the
maximum number of hops before a message should stop forwarding. The time
to live (TTL) was the maximum duration that a message may exist before expir-
ing. The storage capacity was the maximum space that a node can use for storing
messages. For our routing method, we used a default prediction window ΔT of 10
hours and a probability threshold of 0.01. The replication factor r was not limited
by default, so the source of a message transferred the messages to any other node
that had a contact probability with the message destination higher than the prob-
ability threshold. All protocols (except direct and random) used the index-message
optimization method above.
1.1.4.3 Message Generation
After each contact event in the contact trace, we generated a message with a given
probability; we chose a source node and a destination node randomly using a uni-
form distribution across nodes seen in the contact trace up to the current time.
When there were more contacts during a certain period, there was a higher like-
lihood that a new message was generated in that period. This correlation is not
* We tried to use a general network simulator (ns2), which was extremely slow when simulating
a large number of mobile nodes (in our case, more than 5000 nodes) and provided unnecessary
detail in modeling lower-level network protocols.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-26-2048.jpg)
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© 2011 by Taylor & Francis Group, LLC
more transmissions (Figure 1.13). Our protocol was not as sensitive to the pre-
diction window as it was to probability threshold. When the prediction window
increased to one hour or longer, the delivery ratio and the number of messages
transmitted increased only slightly. Therefore, the contact probability within one
hour or longer did not change much.
1.1.5 Related Work
Fall [6] presents an overview of DTNs. It gives examples of delay-tolerant networks:
terrestrial mobile networks, exotic media networks (e.g., satellite, deep space), mili-
tary ad-hoc networks, and sensor networks. The challenges of those networks are
high latency, disconnection, and long queuing time. Fall focuses on the interoper-
ability of heterogeneous networks (e.g., Internet, satellite networks, Intranet, or
ad-hoc networks). The author proposes to use a DTN gateway to connect different
networks, and defines naming of network entities.
Chuah et al. [4] extends the naming convention in Fall’s DTN architecture
framework [6] to further divide a network region into groups. This work also
discusses details of neighbor discovery, gateway selection, mobility management,
and route discovery.
Jain et al. [12] later extend Fall’s framework [6]. They propose and evaluate sev-
eral routing algorithms in two example scenarios: remote village and city bus. Both
scenarios have predictable connectivity. The remote village has a dial-up connection
0
0.5
1
1.5
2
2.5
3
3.5
0.01 0.1 1 10 100
Number
of
Messages
Transmitted
(million)
Prediction Window (hours)
Figure 1.13 Prediction window impact on message transmission of timely con-
tact routing. We used prediction window ΔT = 10 hours for other plots.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-35-2048.jpg)
![20 ◾ Libo Song and David F. Kotz
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They conclude that in networks with limited resources, the smarter algorithms (ED,
EDLQ, and EDAQ) may provide a significant benefit. They also found that global
knowledge may not be required for good performance, since EDLQ performed as well
as EDAQ in many cases. The routing problem, however, when the contacts are predict-
able, is relatively simple, especially in the remote village scenario, where the village com-
municates with only the city through three different routes. The LP algorithm provides
only a theoretical analysis. In practice, the required information is not available.
Li and Rus [18] propose algorithms to guide mobile nodes’ movements for com-
munication in disconnected mobile ad hoc networks. Two algorithms were studied.
The first assumes that mobilities and locations are known to all nodes. The second
one is more generalized and does not assume this knowledge. Li and Rus describe
a network situation in which nodes are moving with their tasks and may move to
other nodes for message delivery. The proposed algorithms avoid traditional wait-
ing and retry schemes. The big disadvantage is that the algorithms require users to
move based on the needs of messages. This means that users (people) need to be
aware of the messages and decide if relay is necessary. The algorithms are tools to
aid the user to make the movement decision.
Wang and Wu [26] studied two basic routing approaches (direct delivery and
flooding) and propose a scheme based on delivery probability. They found that
their delivery-probability scheme achieves a higher delivery ratio than either of the
basic routing approaches. They also studied the average delay and transmission
overhead for all three delivery methods. Although the flooding approach has the
lowest average delay, the delivery ratio suffers because excessive message duplica-
tions exhaust storage buffers. The authors discuss a mobile sensor network in which
all sensor nodes transmit messages to sink nodes. Messages can be delivered to any
sink node. The limited number of destinations enables the simple probability esti-
mation of the proposed scheme.
LeBrun et al. [16] propose a location-based, delay-tolerant network routing
protocol. Their algorithm assumes that every node knows its own position, and
the single destination is stationary at a known location. A node forwards data to
a neighbor only if the neighbor is closer to the destination than its own position.
Our protocol does not require knowledge of the nodes’ locations, and it learns their
contact patterns.
Leguay et al. [17] use a high-dimensional space to represent a mobility pattern,
then route messages to nodes that are closer to the destination node in the mobility
pattern space. Node locations are required to construct mobility patterns.
Musolesi et al. [20] propose an adaptive routing protocol for intermittently con-
nected mobile ad hoc networks. They use a Kalman filter to compute the prob-
ability that a node delivers messages. This protocol assumes group mobility and
cloud connectivity; that is, nodes move as a group, and among this group of nodes
a contemporaneous end-to-end connection exists for every pair of nodes. When
two nodes are in the same connected cloud, destination-sequenced distance-vector
(DSDV) [21] routing is used.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-37-2048.jpg)
![Routing in Mobile Opportunistic Networks ◾ 21
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Erasure coding [11,25] explores coding algorithms to reduce message replicas.
The source node replicates a message m times, then uses a coding scheme to encode
them in one big message. After replicas are encoded, the source divides the big
message into k blocks of the same size and transmits a block to each of the first
k encountered nodes. If m of the blocks are received at the destination, the mes-
sage can be restored, where m < k. In a uniformly distributed mobility scenario,
the delivery probability increases because the probability that the destination node
meets m relays is greater than it meets k relays, given m < k.
Island Hopping [22] considers a network topology that consists of nodes of a
set of connected subgraphs, or connectivity islands, and a set of edges representing
possible node movements between those islands. Nodes learn the entire graph by
exchanging their views of the network based on prior node movement.
We did not implement and evaluate these routing protocols because either
they require unrealistic future information [12], controllable mobile nodes [18], or
domain-specific information (location information) [16,17]; they assume certain
mobility patterns [20,22]; or they present orthogonal approaches [11,25] to other
routing protocols.
A recent study by Conan, Leguay, and Friedman [5] is similar to our work. They
use the intercontact time to calculate the expected delivery time. Their relay strategy
is based on the minimum expected delivery time. The difference from our work is
that our relay strategy is based on the maximization of the contact probability within
a given time interval. They also used the Dartmouth data, as well as two other data
sets for their simulation. They constructed a subset of the Dartmouth data set, in
which all users appear on the network every day. Therefore, their Dartmouth data
simulation results have higher delivery ratios and shorter deliver delays than ours.
More recently, Yuan et al. [27] propose Predict and Relay, which uses a time-
homogeneous semi-Markov process model to predict the future contacts of two
specified nodes at a specified time. With this model, a node estimates the future
contacts of its neighbors and the destination, and then selects a proper neighbor as
the next hop to forward the message. A synthetic mobility model is used for their
simulation. Nodes move among a set of landmark locations with a given prob-
ability. It is difficult to compare our work with theirs because they use a different
mobility model.
1.1.6 Summary
We simulated and evaluated several routing protocols in opportunistic networks.
We propose a prediction-based routing protocol for opportunistic networks. We
evaluate the performance of our protocol using realistic contact traces and compare
to five existing routing protocols: three simple protocols and two other prediction-
based routing protocols.
Our simulation results show that direct delivery had the lowest delivery ratio,
the fewest data transmissions, and no meta-data transmission or data duplication.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-38-2048.jpg)
![22 ◾ Libo Song and David F. Kotz
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Direct delivery is suitable for devices that require extremely low power consump-
tion. The random protocol increased the chance of delivery for messages otherwise
stuck at some low-mobility nodes. Epidemic routing delivered the most messages.
The excessive transmissions and data duplication, however, consume more resources
than portable devices may be able to provide.
Direct-delivery, random, and epidemic routing protocols are not practical for
real deployment of opportunistic networks because they either had an extremely
low delivery ratio or had an extremely high resource consumption. The prediction-
based routing protocols had a delivery ratio more than 10 times better than that
for direct-delivery and random routing, and they had fewer transmissions and used
less storage than epidemic routing. They also had fewer data duplications than
epidemic routing.
All the prediction-based routing protocols that we evaluated had similar per-
formance. Our method had a slightly higher delivery ratio but more transmissions
and higher storage usage. There are many parameters for prediction-based routing
protocols, however, and different parameters may produce different results. Indeed,
there is an opportunity for some adaptation; for example, high-priority messages
may be given higher transfer and replication probabilities to increase the chance of
delivery and reduce the delay, or a node with infrequent contact may choose to raise
its transfer probability.
We must note that our evaluations were based solely on the Dartmouth traces.
Our findings and conclusions may or may not apply to other network environments,
because users in different network environments may have distinct mobility pat-
terns and thus distinct handoff patterns. We also note that our traces were not
motion records, our contact model was based on association records, and messages
were synthetically generated. We believe, however, that our traces are a good match
for the evaluation of handoff predictions and bandwidth reservations. A more pre-
cise evaluation may need motion traces—that is, the physical location of users and
models to determine users’ connectivity.
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[15] David Kotz, Tristan Henderson, and Ilya Abyzov. CRAWDAD data set dart-mouth/
campus. http://crawdad. cs. dartmouth.edu/dartmouth/campus, December 2004.
[16] Jason LeBrun, Chen-Nee Chuah, Dipak Ghosal, and Michael Zhang. Knowledge-
based opportunistic forwarding in vehicular wireless ad hoc networks. In Proceedings of
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[17] Jeremie Leguay, Timur Friedman, and Vania Conan. Evaluating mobility pattern space
routing for DTNs. In Proceedings of the IEEE International Conference on Computer
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[18] Qun Li and Daniela Rus. Communication in disconnected ad-hoc networks using
mes
sage relay. Journal of Parallel and Distributed Computing, 63(1):75–86, January
2003.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-40-2048.jpg)
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© 2011 by Taylor & Francis Group, LLC
[19] Anders Lindgren, Avri Doria, and Olov Schelen. Probabilistic routing in intermittently
connected networks. In Workshop on Service Assurance with Partial and Intermittent
Resources (SAPIR), pp. 239–254, 2004.
[20] Mirco Musolesi, Stephen Hailes, and Cecilia Mascolo. Adaptive routing for intermit
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[21] C. E. Perkins and P. Bhagwat. Highly dynamic destination-sequenced distance-vector
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tions and Networks (SECON), September 2006.
[23] Jing Su, Ashvin Goel, and Eyal de Lara. An empirical evaluation of the student-net
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[24] Amin Vahdat and David Becker. Epidemic routing for partially-connected ad hoc net
works. Technical Report CS-2000-06, Duke University, July 2000.
[25] Yong Wang, Sushant Jain, Margaret Martonosi, and Kevin Fall. Erasure-coding based
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[26] Yu Wang and Hongyi Wu. DFT-MSN: The delay fault tolerant mobile sensor network
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Ad Hoc Networking and Computing (MobiHoc), May 2009.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-41-2048.jpg)
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Thabotharan Kathiravelu and Arnold Pears
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2.1 Introduction
Opportunistic networking explores the data transmission potential of small mobile
devices, such as mobile phones and Personal Digital Assistants (PDAs). Small
handheld wireless devices carried by humans form opportunistic networks and can
utilize intermittent contact with other devices to exchange data [10,28]. Potential
opportunistic networks arise as device users congregate and disperse [38]. For
example, when people travel in a subway train or in a commuter bus they are in
close proximity to other passengers and their mobile devices can contact each other
to transfer information
—for instance, an MP3 file. Figure 2.1 shows the typical
formation of an opportunistic networking environment and how the content of
interest is forwarded opportunistically.
Current research in opportunistic networks ranges from opportunistic for-
warding strategies, through modeling device contacts, to identifying appropriate
use cases and evaluation scenarios, and developing theoretical and mathematical
models. Performance modeling and analysis are of both practical and theoreti-
cal importance. Since activities in opportunistic networking are still in their early
stages, performance modeling is an essential ingredient of opportunistic network-
ing research. Developing better methods for measuring system performance is also
of great importance. Performance modeling helps to identify key challenges in both
design and research methodologies, as well as to gain insight into the behavior of
opportunistic networking systems.
Figure 2.1 A typical example of formation of opportunistic contacts and the
opportunistic forwarding of content of interest.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-43-2048.jpg)
![State of the Art in Modeling Opportunistic Networks ◾ 27
© 2011 by Taylor & Francis Group, LLC
Simulation-based studies are widely used, and one of the main objectives of simu-
lations is to provide support for new ideas. Simulation experiments explore the char-
acteristics of opportunistic systems in a wide range of potential deployment scenarios
and help developers to evaluate systems prior to deployment. Researchers have been
actively studying device contact patterns, analyzing their frequency, duration, and pre-
dictability in order to evaluate mechanisms for the exchange of content among peers.
Modeling and performance evaluation constitute two major research activi-
ties. Modeling device contacts is one direction of research, where new models that
mimic pairwise device contacts in opportunistic networking environments have
been proposed [34,45]. Validating the performance of opportunistic protocols and
applications is another direction of research activity. This involves developing, test-
ing, and validating protocols and applications and identifying factors that influence
opportunistic content distribution.
Intermittent connectivity between mobile nodes and the behavioral patterns of
users make modeling and measuring the performance of opportunistic networks
a challenging job. High-fidelity models are needed in order to establish the feasi-
bility of data forwarding protocols and content distribution schemes, to predict
performance boundaries for opportunistic applications as well as to characterize the
power and memory behavior of the network, transport, and application protocols.
A significant challenge in the simulation of opportunistic networks is modeling the
underlying pairwise contacts between nodes. Ideally, simulations should closely
emulate the behavior of “real” networks.
In the remainder of this chapter we provide an overview of the state of the art
in modeling opportunistic network connection structures and pairwise connectiv-
ity. We summarize work in analyzing pairwise contacts in collected opportunistic
connectivity traces and their findings. We then describe the role of mobility models
in modeling contacts in the Mobile Ad hoc Networking research community and
argue that new models are needed for opportunistic network research. We introduce
connectivity models as one feasible approach to modeling contact in opportunistic
networks. The scope of the approach is illustrated using a case study that explores
the impact of variation in connectivity properties of the underlying network on an
application that distributes content to participants in the network.
2.2 Background
2.2.1 Trace Collection and Analysis
Collecting interdevice contact traces has gained much attention in Mobile Ad hoc
Networks (MANET) and opportunistic networking research [10,41]. The main
purpose of trace collection is to characterize interdevice contact patterns. Such
characterizations are then used to validate new protocols and applications. Many
researchers are convinced that collected traces will reveal many interesting facts](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-44-2048.jpg)
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Thabotharan Kathiravelu and Arnold Pears
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about opportunistic contacts among devices [10,39,41]. Figure 2.2 shows the prepa-
ration activities prior to opportunistic contact trace collection in an academic con-
ference in December 2007.
In 2004, Su et al. began investigating the feasibility of opportunistic data for-
warding using human connectivity traces that were collected using PDAs [58].
Pioneering work in collecting true opportunistic contact traces and analyzing them
for their underlying properties and the feasibility of forwarding using opportunis-
tic contacts was carried out by Chaintreau et al. in 2005 [12]. Chaintreau et al.
have analyzed three publicly available traces from the University of California, San
Diego (UCSD) [42], Dartmouth University [26], and the University of Toronto
[58]. UCSD traces include the client-based logs of the visibility of access points for
a three-month period, while the Dartmouth University traces include SNMP* logs
from access points for a four-month period. The University of Toronto trace set was
collected using 20 Bluetooth-enabled PDAs carried by students for a period of 16
days.
In addition to these traces, Hui et al. have conducted their own experiments
with iMote devices and have collected three different contact trace sets [28]. Of
these three trace sets, the Intel and Cambridge traces were collected in research lab
settings, whereas the iMotes were carried by researchers and doctoral students. The
Infocom trace set was collected at the IEEE INFOCOM 2005 conference and the
iMotes were carried by the conference participants.
iMotes are a common platform for connectivity trace collection activities.
Designed by Intel, they use Bluetooth wireless technology to log their device
* Simple Network Management Protocol.
Figure 2.2 Small mobile devices with Bluetooth wireless connectivity are being
prepared for trace collection in a conference environment in December 2007.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-45-2048.jpg)
![State of the Art in Modeling Opportunistic Networks ◾ 29
© 2011 by Taylor & Francis Group, LLC
discovery and contact details with other Bluetooth-enabled devices [10,41]. Mobile
phones and PDAs are also commonly used in collecting connectivity traces and are
a good choice in terms of memory and battery power, but, at the same time, they
are expensive to deploy on a larger scale [35].
All these collected traces were analyzed for their interdevice connection proper-
ties in order to understand the constraints of opportunistic data transfer, and two
new terms—contact time and inter-contact time—were defined and characterized:
Contact Time is the time interval during which two mobile devices are in each
others’ communication range and communicate with each other. In experiments
based on opportunistic networks, contact times are often recorded and used as
a measure for estimating the amount of data that could possibly be transferred.
Contact times also are used to determine the pattern of underlying probabilistic
distributions over time.
Inter-Contact Time is the time interval measured between two consecutive con-
tactswhentwomobiledevicesareincontactwitheachotherintermittently.Theinter-
contact time values and their distribution over the period of time are two important
pieces of information. The likelihood that a device will be encountered again in a
given time period can also be determined or estimated from these values.
In Figure 2.3, we characterize the nature of the contact and inter-contact times
of two nodes, n1 and n2, that meet each other intermittently.
Many others followed the path of Chaintreau et al. in collecting traces from dif-
ferent environmental settings and have analyzed the inter-device contact patterns
and their distributions. Leguay et al. [41] did an experimental study in the city of
Cambridge with 54 Bluetooth-enabled iMote devices that were carried by students
or fixed at popular places. Contact data was logged for a period of 13 days. The
connectivity information from this experiment was then used in investigating the
feasibility of a citywide content distribution network. By categorizing users with
different behavioral patterns, they analyzed the effectiveness of this user population
in distributing data bundles.*
* Data bundle is a term commonly used in delay-tolerant networking [6,9,32] to refer to aggre-
gated data. The same term has also been adopted by opportunistic networking researchers to
refer to clusters of data packets [32,41].
Contact time (t2–t1) Contact time (t4–t3) Contact time (t6–t5)
Time t2
Time t1
Nodes n1 & n2 n1 & n2
Intercontact time (t3–t2) Intercontact time (t5–t4)
n1 & n2 n1 & n2 n1 & n2 n1 & n2
Time t4
Time t3 Time t6
Time t5
Figure 2.3 Characterization of contact and inter-contact times for two nodes n1
and n2, which meet intermittently.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-46-2048.jpg)
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Thabotharan Kathiravelu and Arnold Pears
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LeBrun et al. [39] have explored the feasibility of disseminating information
using transit buses on the University of California Davis campus. Each bus is
equipped with a Bluetooth content-distribution cache called BlueSpot. Any device
with a Bluetooth-enabled interface can connect to these caches and download files
while the bus is en route. They predict the provision of services like on-demand
downloads of iTunes® music files as a future killer application.
The Reality Mining project [19] at MIT* collected communication proximity,
location, and activity information of 100 selected participants over a nine-month
period. Each participant was given a mobile phone that had both Bluetooth and
cellular network accessibility. This research looked at the mobile device interactions
in many directions.
In Table 2.1 we present some opportunistic contact traces that are publicly avail-
able at the CRAWDAD† web site. Cambridge1 was collected by Leguay et al. [41],
Intel, Cambridge2, and Infocom were collected by Chaintreau et al. [12], and BSpot1,
BSpot2, and BSpot3 were collected by LeBrun et al. [39]. The Access Technology
mentioned as BT in the table refers to Bluetooth wireless technology [21].
The analysis of the underlying probabilistic distributions of contact and inter-
contact times of all collected traces have helped researchers in developing theoretical
foundations for opportunistic forwarding algorithms and strategies [11,13]. While
trace collection has been, and remains, a popular activity, traces typically have rela-
tively short time periods and small populations, due to the logistic challenges associ-
ated with large-scale experiments [29,40,41]. Short logging periods, lack of variation
in the device population, and other statistical properties limit the usefulness of many
existing traces [60]. Leguay et al. [41] describe the difficulties caused by device fail-
ures due to memory overflows, drained battery power, and so on in trace collection
processes. Nordström et al. [53] provide insight into the challenges in measuring
human mobility and collecting connectivity traces and caution researchers about
the limitations inherent in using publicly available connectivity trace sets.
2.2.2 Modeling Contacts
Many research studies in MANET and opportunistic networks are dependent on
simulation-based studies to test and validate new hypothesis and ideas. Modeling
inter-device contacts is essential in these studies in order to tell the simulation
engine how the contacts are made between simulation entities [8,31,37,44].
Researchers have so far been using synthetic mobility models and human contact
traces as input for simulation based studies. Recently, there have been attempts to
model contacts more accurately by refining mobility models and modeling contacts
using the measured properties of human connectivity traces [36,65]. We describe
* Massachusetts Institute of Technology.
† Community Resource for Archiving Wireless Data at Dartmouth (CRAWDAD) http://
crawdad.cs.dartmouth.edu.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-47-2048.jpg)
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Thabotharan Kathiravelu and Arnold Pears
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mobility models in detail and then look at the recent extensions to these models for
intermittently connected mobile networks. We conclude by discussing an alterna-
tive approach, connectivity models.
2.2.3 Mobility Models
Mobility models generate plausible sequences of inter-device contacts synthetically
based on a set of parameters that characterize the environment. Though catego-
rizing any mobility model as realistic is difficult, modeling device mobility is an
essential part of any simulation study. Synthetic mobility models are often prefer-
able since they allow the researcher to alter the parameters of the simulation set and
reproduce simulation results easily.
The random waypoint (RWP) mobility model is one of the most widely used
single-entity random movement methods [4]. In RWP, nodes move in a given
direction with a given speed and pause occasionally to change direction or speed.
Random walk and random direction are also two widely used single-entity mobil-
ity models [8,32,55]. A good survey of synthetic mobility models, excluding a few
of the most recent mobility models, can be found in [8].
It has been shown [8] that traditional synthetic mobility models do not model
node mobility in a manner that causes the contact and inter-contact time distribu-
tions of simulated nodes to decay exponentially over time [5,57,64]. Such a behav-
ior is very different from what has been observed in field tests [10]. Analysis and
systematic studies of the stochastic properties of earlier models have identified flaws
in modeling, and new mobility models that mimic real-world environments and
related movement patterns have been proposed [27,31,36,37,46].
Jardosh et al. propose a mobility model that includes obstacles in the node path
in order to mimic mobility in a more realistic environment [31]. In addition to
obstacles along the path of node movement, MobiREAL [37] considers the behav-
ioral changes of nodes due to the surroundings, time of the day, and so on, and uses
a rule-based model to describe the movement patterns of nodes.
The weighted waypoint mobility model [27] recognizes that people do not
choose their waypoints randomly. It models this behavior by defining popular loca-
tions in the simulation field and their related popularity weight values according to
the probability of choosing these locations as the next destination. In this Markov
chain–based model, the selection probability of a new destination is determined
based on the current location and time.
Mobility models could also be designed based on the observed statistical prop-
erties from human mobility traces. The observed statistical properties can then be
fed into the mobility model so that the generated interdevice connectivity resembles
the same statistical properties [36,65].
Kim et al. [36] describe a method for extracting user mobility tracks from
recorded Wi-Fi traces. They have examined the tracks in the Wi-Fi traces and
were able to extract information such as speed, pause times, destination transition](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-49-2048.jpg)
![State of the Art in Modeling Opportunistic Networks ◾ 33
© 2011 by Taylor & Francis Group, LLC
probabilities, and waypoints between destinations. This information is then used in
forming an empirical model that can be used to generate synthetic tracks of move-
ments of nodes [36]. They have validated their model by performance comparisons
between trace locations and the locations determined by users carrying both GPS
and 802.11 devices.
A new mobility modeling technique has emerged recently based on social net-
work theory [43]. Musolesi and Mascolo devised their mobility model using human
social networking concepts and human connectivity traces as the basis for the rep-
resentation of human movement [46]. Another group’s mobility model, also based
on the social networking theory that allows nodes to be grouped depending on
their social relationships and measured network structures, called the community-
based mobility model, was later proposed by Musolesi and Mascolo [44].
Karlsson et al. [32] used random waypoint and random walk mobility models
[8] to model node mobility to study the performance of a receiver-driven delay-
tolerant content broadcasting environment.
2.2.4 New Generation Models
Recent studies on various networks, such as the Internet and biological networks,
have revealed that these networks have fundamentally the same properties as social
networks [1,22,48,50]. Empirical studies further reveal that these social networks
contain recurring elementary interaction patterns between small groups of nodes
that occur substantially more often than would be expected in random networks
that are determined by Poisson distributions. These recurring interactions also
carry significant information about the network’s evolution and functionality. We
can also observe similar recurring interactions between nodes in time-aggregated
opportunistic field connectivity traces. Please refer to Figure 2.7 for a pictorial view
of clusters of node contacts observed in a typical opportunistic field trace set.
The set of clusters of contacts formed by the time-aggregated contacts between
pairs of nodes in a connectivity trace set is a new concept in opportunistic net-
working, even though the concept of clusters is often used in network analysis and
graph theory. We view the existence of clusters as follows: Suppose we take a time-
aggregated opportunistic connectivity trace set. This aggregated trace set can be
represented by a graph, G(V, E), with a set of vertices V representing the nodes and
a set of edges, E, representing the aggregated contacts between the node pairs. The
edge weights represent the aggregated contact times between pairs of vertices.
A subset V′ ∀ V of the vertex set induces a subgraph G[V′] = (V′, E′) with
E′ = {( u,v ) | u,v ∈ V′ }. A nested decomposition of G by removing edges is a finite
sequence (V0,V1,V2,...,Vk) of subsets of subgraphs of V such that V0 = V, Vi+1 is a
subgraph of Vi for i Ψ k and Vk ≠ 0.
We refer to the subgraphs that arise as a result of subsequent decompositions as
the set of clusters of nodes. The more edges that are removed, the more clusters are
formed, which eventually results in decomposing the graph into individual nodes.](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-50-2048.jpg)
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Thabotharan Kathiravelu and Arnold Pears
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There exist many open source packages, such as iGraph [18] and NetworkX [23],
which can be incorporated easily into scripting languages and be used for visual-
izing network structures and varying natures of clusters of contacts between nodes.
Please refer to Figure 2.7 for a sample diagram generated by the iGraph [18] pack-
age with the application of the clustering algorithm of Clauset et al. [15]. Many
other stand-alone programs and packages are available for the manipulation of net-
working traces, their properties, community identification, and visualization [52].
Two important terms need to be mentioned here: the intra-cluster edges and the
inter-cluster edges. An edge (u, v) is an intra-cluster edge if both u and v belong to the
same cluster—otherwise it is an inter-cluster edge. In Figure 2.7, as mentioned, one can
observe the existence of node clusters, intra-cluster edges, and inter-cluster edges in a typical
opportunistic contact trace set after successive removal of edges of less edge weights.
We hypothesize that these cluster structures will be the backbone of the net-
work for these reasons. The edges that remain in the graph are of higher weights
and many of them are aggregated values of repeated contacts over the period of
time. They represent the recurring nature of contacts that exist between the nodes
in a diurnal fashion, and such contacts are capable of forwarding content from one
node to another. In addition, ensuring that the content gets distributed to these
nodes will ensure that the content gets distributed to the larger user population,
since we have seen that these nodes had contacts with other nodes, too, although
not as often as they do with the nodes in their own cluster. The ability to model the
network at such cluster levels will enable the researcher to model the backbone of
the network and the network connections.
Detecting clusters in opportunistic networks allows one to extract information
in a more efficient way. In larger networks, identifying the inherent cluster structures
narrows down the exploration work to be done. One can use the insight from social
sciences to characterize clusters. When used in the analysis of large collaboration net-
works, clusters reveal the contact patterns, repeated contacts, the informal organiza-
tion, and the nature of information flow through the whole system [30,49,51].
The algorithm introduced by Newman [49] for identifying communities of
contacts is based on the edge betweenness. The edge betweenness measures the frac-
tion of all shortest paths passing on a given edge. By removing an edge with high
betweenness, one can progressively split the whole network into disconnected com-
ponents. Further improvements over this algorithm enable researchers to precisely
divide a network into a set of clusters [15,51].
As new network features such as resilience and cluster structures emerge, new
models that can model graphs with these characteristics and their inherent prop-
erties are required. This will enable researchers to model not only contacts in the
network but also the substructures (such as clusters of contacts) that are present in
the network.
Erdös and Rényi pioneered an approach [20] based on random graphs, where
each pair of vertices in the graph is connected by an edge with a given probabil-
ity. Such models, which are approximated by Poisson processes, are not capable](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-51-2048.jpg)
![State of the Art in Modeling Opportunistic Networks ◾ 35
© 2011 by Taylor & Francis Group, LLC
of generating graphs that resemble human dynamics such as social networking
and entertainment [2]. Random graphs proposed by Watts and Strogatz [63], and
Albert and Barabási [1] exhibit properties like power-law distributions [16] in edge
degrees, freedom from scale, and small diameter, and so on, which reflect the com-
plex interaction patterns determined empirically in human dynamics.
Delay-tolerant networks (DTNs) propose a store-carry-and-forward message
switching approach as a viable solution to the problem of intermittent connectiv-
ity. Devices store messages until they encounter another suitable device, and the
devices that receive messages keep on forwarding to other devices along a path that
eventually delivers data to the intended recipient. In order to achieve this, the DTN
architecture introduces a protocol layer called the bundle layer on top of the region-
specific lower layers of the protocol stack. This bundle layer handles aggregating
data into bundles and delivering them across multiple regions [9].
Characterizing interdevice contacts in delay-tolerant networking would benefit
the opportunistic networking community greatly. In a recent work, Conan et al.
[17] looked at three reference DTN contact data sets and, based on the statistical
analysis on these data sets for their pair-wise inter-contact times, have character-
ized the heterogeneity in contact and inter-contact times. Conan et al. found that
the distributions of inter-contact times are well modeled by log-normal curves for a
large number of node pairs.
The node movement patterns in a simulation’s coordinate space indirectly result
in patterns of pairwise node contacts of varying duration. Connectivity models
generate pairwise contacts in the simulation of varying durations using parameters
drawn from field traces, obviating the use of a mobility model. The motivation
behind this approach is that mobility models are a high-overhead approach to
generating pairwise node connectivity data. Therefore, why should the temporal
patterns of connectivity not be modeled directly, based on estimated parameters?
Generating connectivity information directly relieves the designer of the complex-
ity associated with trying to develop an appropriate model and define its parame-
ters. Conducting experiments with varying numbers of user populations and device
connectivity properties, and the comfort of reproducing traces, rather than con-
ducting real field traces, are other advantages of this approach.
2.2.5 Simulation Tools for Modeling and Analysis
Since opportunistic networking is considered as a subclass of MANET research, it
has adopted the simulation and other modeling tools used by the MANET com-
munity for testing and validating applications and systems. As in MANET research
studies, the ease of setup, repeatability of experiments, and the ease of variation
in the experimental parameters make simulation-based studies the first choice of
opportunistic networking researchers in support of new hypotheses and ideas.
Kathiravelu and Pears [33] used the Jist/SWANS (Java in Simulation
Time/ScalableWirelessAdhocNetworkSimulator)simulator,whichwasdeveloped](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-52-2048.jpg)
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Thabotharan Kathiravelu and Arnold Pears
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by Rimon Barr [3], to model and a scenario-based study of an opportunistic net-
working environment in order to characterize the contact patterns between mobile
nodes. In Jist/SWANS, the simulation code written in Java is compiled into a set of
class files as usual and then rewritten by the bytecode rewriter into simulation code.
The rewritten code is then executed by the simulation engine. Further extensions,
such as run time visualization, newer mobility model implementation, and so on,
have also been added to Jist/SWANS simulator [14] by researchers. SWANS, which
is built on top the JiST simulator, helps researchers to simulate different wireless
contact scenarios with different mobility models, such as random waypoint, ran-
dom walk, and teleport mobility models [33]. The layered architecture of SWANS
enables researchers to further extend it according to their needs [33].
Helgason and Jonsson [25] have described their work in customizing the
OMNeT++ [61] simulator to model and simulate opportunistic network contacts.
They employed two different approaches to simulating opportunistic networking.
In the first approach, which is called the mobility-driven method, mobility patterns
of nodes are specified in a mobility trace Þle. In the second approach, which is
called the contact-driven method, the time of node contacts and their durations are
specified in a contact trace file. Musolesi and Mascolo [47] also used the OMNeT++
simulator to validate the performance of a new protocol called CAR (Context-
Aware Routing) for DTNs using the community-based mobility model [44,45].
In addition, many researchers develop their own simulation engines to carry out
experimental studies in opportunistic networks [24,41]. Since very little informa-
tion is available about these simulation tools, it is not possible to describe them in
detail here.
Haggle testbed is a networking architecture designed to cater to the needs of
mobile users by providing seamless network connectivity and application func-
tionality in highly mobile environments [56,59]. Haggle separates the application
logic from transport binding so that the applications can still be fully functional in
highly dynamic mobile environments [59]. Haggle takes care of data handling and
communications by adapting to the best available networking environment at that
time based on user preferences [59].
2.2.6 A Connectivity Model
In opportunistic networking environments, the aim is to optimize the connection
opportunities, and any model that attempts to represent such an environment should
consider the factors that affect the most important features of real traces: the inter-
contact time and the contact time [10]. Previous analysis of opportunistic contact traces
indicates the significance of these two values, and any synthetic generation process
should be capable of reproducing the distributions of these two values.
We propose that connectivity models should be based on the analysis of connectiv-
ity patterns in real networking environments. Analysis of these traces for their stochastic
properties allows us to derive probability distributions to model internode relationships](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-53-2048.jpg)
![State of the Art in Modeling Opportunistic Networks ◾ 37
© 2011 by Taylor & Francis Group, LLC
(the so-called small world properties of social networks) as well as the probability of a
relationship resulting in two nodes being connected at a given point in time.
Our connectivity model is constructed in two phases:
(i) We determine the social connectedness of the node set.
(ii) After the device relationship network has been determined, the frequency of
connection events between two related nodes results in a connectivity trace
with the desired properties.
We define a connectivity model M,
M K P P N
R C
= ( )
, , ,
where
N is the number of nodes in the simulation.
K is a set of clusters [K1..Kk], for a network with k clusters.
PR(A, B), is the relationship function defining the probability that any two
devices A and B are related.
PC(e), is a connectivity function defining the likelihood that two nodes related
by an edge e establish a connection. Here e ∈ E, the set of edges deter-
mined by applying the relationship function PR to all pairs of nodes in
the model.
We define PR, in terms of λ, the intra-cluster relationship distribution, and 𝜙,
the inter-cluster relationship distribution.
P
K
K K
R
i
i j
( )
A B
A B
A B
, =
, ∈
∈ ∈ ≠
λ
φ
where
where and and i j
⎧
⎧
⎨
⎪
⎩
⎪
(2.1)
From Equation (2.1), PR(A, B) is used to compute a set of edges E that defines
a graph representing the relationships between simulation nodes. If the parameters
are chosen correctly, the graph obtained by applying Equation (2.1) to all node
pairs will have a cluster and internode edge density to the weighted aggregated
graph of the original field trace. See Nykvist and Phanse [54] for an example of
such a connection graph.
2.2.7
Application of the Connectivity Model and
a Content Distribution Scenario–Based Study
The scenario uses parameters gleaned from the Cambridge1 iMote connectivity
traces, published in [41]. It is one of a collection of connectivity traces available from
CRAWDAD and is a truly opportunistic contact trace set with a comparatively
large number of contacts and devices. From the Cambridge1 data we extracted](https://image.slidesharecdn.com/1134846-250523022515-1d814240/75/Mobile-Opportunistic-Networks-Architectures-Protocols-And-Applications-1st-Edition-Mieso-K-Denko-54-2048.jpg)
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- 9. Auerbach Publications Taylor &Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2011 by Taylor and Francis Group, LLC Auerbach Publications is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-13: 978-1-4200-8813-7 (Ebook-PDF) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmit- ted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright. com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the Auerbach Web site at http://www.auerbach-publications.com
- 10. v © 2011 byTaylor & Francis Group, LLC Contents Preface............................................................................................................vii About the Editor.............................................................................................xi 1 Routing in Mobile Opportunistic Networks...........................................1 LIBO SONG AND DAVID F. KOTZ 2 State of the Art in Modeling Opportunistic Networks.........................25 THABOTHARAN KATHIRAVELU AND ARNOLD PEARS 3 Credit-Based Cooperation Enforcement Schemes Tailored to Opportunistic Networks...................................................................51 ISAAC WOUNGANG AND MIESO K. DENKO 4 Opportunism in Mobile Ad Hoc Networking.......................................83 MARCELLO CALEFFI AND LUIGI PAURA 5 Opportunistic Routing for Load Balancing and Reliable Data Dissemination in Wireless Sensor Networks. ......................................115 MIN CHEN, WEN JI, XIAOFEI WANG, WEI CAI, AND LINGXIA LIAO 6 Trace-Based Analysis of Mobile User Behaviors for Opportunistic Networks................................................................137 WEI-JEN HSU AND AHMED HELMY 7 Quality of Service in an Opportunistic Capability Utilization Network............................................................................173 LESZEK LILIEN, ZILL-E-HUMA KAMAL, AJAY GUPTA, ISAAC WOUNGANG, AND ELVIRA BONILLA TAMEZ 8 Effective File Transfer in Mobile Opportunistic Networks.................205 LING-JYH CHEN AND TING-KAI HUANG
- 11. vi ◾ Contents ©2011 by Taylor & Francis Group, LLC 9 Stationary Relay Nodes Deployment on Vehicular Opportunistic Networks.............................................................................................227 JOEL J. P. C. RODRIGUES, VASCO N. G. J. SOARES, AND FARID FARAHMAND 10 Connection Enhancement for Mobile Opportunistic Networks.........245 WEIHUANG FU, KUHELI LOUHA, AND DHARMA P. AGRAWAL Index....................................................................................... 273
- 12. vii © 2011 byTaylor & Francis Group, LLC Preface Opportunistic networks are an emerging networking paradigm where communi- cation between the source and destination happens on the fly and depends on the availability of communication links. In opportunistic networks, intermittent con- nectivity is frequent and mobile nodes can communicate with each other even if a route connecting them did not previously exist. In this type of network, it is not mandatory to have a priori knowledge about the network topology. The network is formed opportunistically based on proximity and network availability, by ran- domly connecting and disconnecting the networks and devices. This networking paradigm heavily benefits from the heterogeneous networking and communication technologies that currently exist and will emerge in the future. Hence, given the advances in wireless networking technologies and the wide availability of pervasive and mobile devices, opportunistic network applications are promising network- ing and communication technologies for a variety of future mobile applications. Mobile opportunistic networks introduce several research challenges in all aspects of computing, networking, and communication. This book provides state-of-the-art research and future trends in mobile opportunistic networking and applications. The chapters, contributed by promi- nent researchers from academia and industry, will serve as a technical guide and reference material for engineers, scientists, practitioners, graduate students, and researchers. To the best of my knowledge, this is the first book on mobile opportu- nistic networking. Thebookisorganizedintotwosectionscoveringdiversetopicsbypresentingstate- of-the-art architectures, protocols, and applications in opportunistic networks. Section 1: Architectures and Protocols Section 1 consists of Chapters 1 through 6, which focus on modeling, networking architecture, and routing problems in opportunistic networking. Chapter 1, Routing in Mobile Opportunistic Networks, is by Libo Song and David F. Kotz, and discusses routing in mobile opportunistic networks. The
- 13. viii ◾ Preface ©2011 by Taylor & Francis Group, LLC simulation of several routing protocols in opportunistic networks are evaluated and discussed. The authors have also presented and evaluated their proposed prediction- based routing protocol for opportunistic networks. This protocol was evaluated using realistic contact traces, and then compared with existing routing protocols. Chapter 2, State of the Art in Modeling Opportunistic Networks, was written by Thabotharan Kathiravelu and Arnold Pears, and discusses the state of the art in modeling opportunistic network connection structures and pairwise contacts. The chapter also introduces connectivity models as an approach to modeling contacts in opportunistic networks, and then illustrates the scope of this approach using case studies. Chapter 3 is entitled Credit-Based Cooperation Enforcement Schemes Tailored to Opportunistic Networks, and was written by Isaac Woungang and Mieso K. Denko. This chapter discusses cooperation enforcement in opportunistic networks. A comprehensive review and detailed comparison of credit-based incentive schemes for mobile wireless ad hoc networks and challenged networks are presented, with the goal of identifying those that are tailored to opportunistic networks. Chapter 4, Opportunism in Mobile Ad Hoc Networking by Marcello Caleffi and Luigi Paura, discusses some fundamental characteristics of opportunistic routing. Most of the popular existing routing protocols and their unique features and suitability to mobile opportunistic networks are discussed. Chapter 5, Opportunistic Routing for Load Balancing and Reliable Data Dissemination in Wireless Sensor Networks by Min Chen, Wen Ji, Xiaofei Wang, Wei Cai, and Lingxia Liao, proposes a novel opportunistic routing protocol for delivering data with load balancing and reli- able transmission capabilities. Performance results in terms of network lifetime and transmission reliability are discussed. Chapter 6 is entitled Trace-Based Analysis of Mobile User Behaviors for Opportunistic Networks, and is written by Wei-Jen Hsu and Ahmed Helmy. This chapter presents a framework that provides a procedural approach to analyzing user behavior based on realistic data in opportunistic net- works. The authors have employed a data-driven approach to develop a fundamen- tal understanding of realistic user behavior in mobile opportunistic networks. Section 2: Services and Applications Section 2 consists of Chapter 7 through 10 and focuses on opportunistic network- ing technologies and applications. Chapter 7, Quality of Service in an Opportunistic Capability Utilization Network by Leszek Lilien, Zille Huma Kamal, Ajay Gupta, Isaac Woungang, and Elvira Bonilla Tamez, presents opportunistic networks (Oppnets) as a paradigm and a technology proposed for realization of opportunistic capability utilization networks. This chapter also presents the use of the service location and planning (SLP) tech- nique for resource utilization with quality of service (QoS) constraints in oppor- tunistic capability utilization networks. It also illustrates the use of Semantic Web technology and its ontologies for specifying QoS requirements in Oppnets using
- 14. Preface ◾ ix ©2011 by Taylor & Francis Group, LLC a novel Oppnet model. Chapter 8, Effective File Transfer in Mobile Opportunistic Networks by Ling-Jyh Chen and Ting-Kai Huang, presents a peer-to-peer approach for mobile file transfer applications in opportunistic networks. This chapter also discusses the combined strengths of cache-based approaches and Infostation-based approaches, as well as the implementation of a collaborative forwarding algorithm to further utilize opportunistic ad hoc connections and spare storage in the net- work. Chapter 9, Stationary Relay Nodes Deployment on Vehicular Opportunistic Networks by Joel J. P. C. Rodrigues, Vasco N. G. J. Soares, and Farid Farahmand, reviews recent advances in the deployment of stationary relay nodes on vehicular opportunistic networks. This chapter also discusses the impact of adding station- ary relay nodes on the performance of delay-tolerant network routing protocols as applied to vehicular opportunistic networks. Finally, Chapter 10, Connection Enhancement for Mobile Opportunistic Networks by Weihuang Fu, Kuheli Louha, and Dharma P. Agrawal, presents analytical approaches for mobility and heteroge- neous connections management in mobile opportunistic networks. Strategies are introduced for network connection selection and message forwarding based on the author’s analytical work. The authors also analyze the improvement of heteroge- neous connections for message delivery performance and have presented a detailed investigation of the current state-of-the-art protocols and algorithms. The research in mobile opportunistic computing and networking is currently in progress in academia and industry. Although this book may not be an exhaustive representation of all research efforts in the area, they do represent a good sample of key aspects and research trends. We owe our deepest gratitude to all the authors for their valuable contributions to this book and their great efforts and cooperation. We wish to express our thanks to Auerbach Publications, the CRC Press staff, and especially to Rich O’Hanley and Stephanie Morkert for their excellent guidance and support. Finally, I would like to dedicate this book to my wife Hana and our children for their support and understanding throughout this project. Dr. Mieso K. Denko November 2009
- 16. xi © 2011 byTaylor & Francis Group, LLC About the Editor Mieso K. Denko received his MSc degree from the University of Wales, United Kingdom and his PhD degree from the University of Natal, South Africa, both in Computer Science. He is a founding Director of the Pervasive and Wireless Networking Research Lab in the Department of Computing and Information Science, University of Guelph, Ontario, Canada. His current research interests include wireless networks, mobile and pervasive computing, wireless mesh networks, wireless sensor networks, and net- work security. His research results in these areas have been published, in international journals, in conference proceedings, and contributed to books. Dr. Denko is a founder/ co-founder of a number of ongoing international workshops and symposia. He has served on several international conferences and workshops as general vice- chair, program co-chair/vice-chair, publicity chair, and technical program com- mittee member. He has guest co-edited several journal special issues in Springer, Wiley, Elsevier, and other journals. Most recently he guest co-edited journal special issues in ACM/Springer Mobile Networks and Applications (MONET) and IEEE Systems Journal (ISJ). Dr. Denko has edited/co-edited multiple books in the areas of pervasive and mobile computing, wireless networks, and autonomic networks. Most recently he co-edited two books: Wireless Quality of Service: Techniques, Standards, and Applications, published by Auerbach Publications, September 2008, and Autonomic Computing and Networking, published by Springer in June 2009. He is Associate Editor of international journals, including the International Journal of Communication Systems (Wiley), the Journal of Ambient Intelligence and Humanized Computing (Springer), and Security and Communication Networks Journal (Wiley). Dr. Denko is a senior member of the ACM and IEEE and the Vice Chair of IFIP WG 6.9. He passed away in April 2010.
- 18. 1 © 2011 byTaylor & Francis Group, LLC Chapter 1 Routing in Mobile Opportunistic Networks Libo Song Google, Inc David F. Kotz Dartmouth College Contents 1.1 Routing in Mobile Opportunistic Networks.................................................2 1.1.1 Routing Protocol...............................................................................3 1.1.1.1 Direct Delivery Protocol......................................................4 1.1.1.2 Epidemic Routing Protocol. .................................................4 1.1.1.3 Random Routing.................................................................4 1.1.1.4 PRoPHET Protocol.............................................................4 1.1.1.5 Link-State Protocol..............................................................5 1.1.2 Timely Contact Probability...............................................................5 1.1.3 Our Routing Protocol........................................................................6 1.1.3.1 Receiver Decision................................................................7 1.1.3.2 Sender Decision...................................................................7 1.1.3.3 Multinode Relay..................................................................7 1.1.4 Evaluation Results.............................................................................8 1.1.4.1 Mobility Traces. ...................................................................8 1.1.4.2 Simulator.............................................................................9 1.1.4.3 Message Generation. ............................................................9
- 19. 2 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC 1.1 Routing in Mobile Opportunistic Networks* Routing in mobile ad hoc networks has been studied extensively. Most of these studies assume that a contemporaneous end-to-end path exists for the network nodes. Some mobile ad hoc networks, however, may not satisfy this assumption. In mobile sensor networks [26], sensor nodes may turn off to preserve power. In wild-animal tracking networks [13], animals may roam far away from each other. Other networks, such as pocket-switched networks [9], battlefield networks [7,18], and transportation networks [1,16], may experience similar disconnections due to mobility, node failure, or power-saving efforts. One solution for message delivery in such networks is that the source passively waits for the destination to be in communication range and then delivers the mes- sage. Another active solution is to flood the message to any nodes in communica- tion range. The receiving nodes carry the message and repeatedly flood the network with the message. Both solutions have obvious advantages and disadvantages: the first may have a low delivery ratio while using few resources; the second may have a high delivery ratio while using many resources. Many other opportunistic routing protocols have been proposed in the litera- ture. Few of them, however, were evaluated in realistic network settings, or even in realistic simulations, due to the lack of any realistic people mobility model. Random walk or random way-point mobility models are often used to evaluate the perfor- mance of those routing protocols. Although these synthetic mobility models have received extensive interest from mobile ad hoc network researchers [2], they do not reflect people’s mobility patterns [10]. Realizing the limitations of using random mobility models in simulations, a few researchers have studied routing protocols in mobile opportunistic networks with realistic mobility traces. In the Haggle project, Chaintreau et al. [3] theoretically analyzed the impact of routing algorithms over a model derived from a realistic mobility data set. Su et al. [23] simulated a set of routing protocols in a small experimental network. Those studies help researchers better understand the theoretical limits of opportunistic networks and the routing protocol performance in a small network (20–30 nodes). Deploying and experimenting with large-scale mobile opportunistic networks is difficult, so we also resort to simulation. Instead of using a complex mobility * This work is based on an earlier work: “Evaluating Opportunistic Routing Protocols with Large Realistic Contact Traces,” in Proceedings of the Second ACM Workshop on Challenged Networks, ©ACM 2007. http://doi.acm.org/10.1145/1287791.1287799. 1.1.4.4 Metrics..............................................................................10 1.1.4.5 Results...............................................................................11 1.1.5 Related Work...................................................................................18 1.1.6 Summary.........................................................................................21 References............................................................................................................22
- 20. Routing in MobileOpportunistic Networks ◾ 3 © 2011 by Taylor & Francis Group, LLC model to mimic people’s mobility patterns, we used mobility traces collected in a production wireless network at Dartmouth College to drive our simulation. Our message-generation model, however, was synthetic. We study protocols for routing messages between wireless networking devices car- ried by people. We assume that people send messages to other people occasionally, using their devices; when no direct link exists between the source and the destination of the message, other nodes may relay the message to the destination. Each device represents a unique person (it is out of the scope of our work to cover instances when a device may be carried by different people at different times). Each message is destined for a specific person and thus for a specific node carried by that person. Although one person may carry multiple devices, we assume that the sender knows which device is the best to receive the message. We do not consider multicast or geocast in this chapter. Using realistic contact traces, which we derived from the Dartmouth College data- set [15], we evaluated the performance of three “naive” routing protocols (direct-deliv- ery, epidemic, and random) and two prediction-based routing protocols, PRoPHET [19] and Link-State [23]. We also propose a new prediction-based routing protocol and compare it to the above protocols. 1.1.1 Routing Protocol A routing protocol is designed for forwarding messages from one node (source) to another node (destination). Any node may generate messages for any other node and may carry messages destined for other nodes. We consider only messages that are unicast (single destination). Delay-tolerant networks (DTN) routing protocols can be described in part by their transfer probability and replication probability; that is, when one node meets another node, what is the probability that a message should be transferred and, if so, whether the sender should retain its copy. Two extremes are the direct-delivery protocol and the epi- demic protocol. The former transfers with probability 1 when the node meets the desti- nation, 0 for others, and never replicates a packet; in effect, the packet only moves when the source meets the destination. The latter uses transfer probability 1 for all nodes and replicates the packet each time it meets another node. Both these protocols have their advantages and disadvantages. All other protocols are between the two extremes. First, we define the notion of contact between two nodes. Then we describe five existing protocols before presenting our own proposal. A contact is defined as a period of time during which two nodes have the oppor- tunity to communicate. Although wireless technologies differ, we assume that a node can reliably detect the beginning and end time of a contact with nearby nodes. A node may be in contact with several other nodes at the same time. The contact history of a node is a sequence of contacts with other nodes. Node i has a contact history Hij, for each other node j, which denotes the historical con- tacts between node i and node j. We record the start and end time for each contact; however, the last contacts in the node’s contact history may not have ended.
- 21. 4 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC 1.1.1.1 Direct Delivery Protocol In this simple protocol, a message is transmitted only when the source node can directly communicate with the destination node of the message. In mobile oppor- tunistic networks, however, the probability for the sender to meet the destination may be low, or even zero. 1.1.1.2 Epidemic Routing Protocol The epidemic routing protocol [24] floods messages into the network. The source node sends a copy of the message to every node that it meets. The nodes that receive a copy of the message also send a copy of the message to every node that they meet. Eventually, a copy of the message arrives at the destination of the message. This protocol is simple but may use significant resources; excessive communication may drain each node’s battery quickly. Moreover, since each node keeps a copy of each message, storage is not used efficiently and the capacity of the network is limited. At a minimum, each node must expire messages after some amount of time or stop forwarding them after a certain number of hops. After a message expires, the message will not be transmitted and will be deleted from the storage of any node that holds the message. An optimization to reduce the communication cost is to transfer index messages before transferring any data message. The index messages contain IDs of messages that a node currently holds. Thus, by examining the index messages, a node only transfers messages that are not yet contained on the other nodes. 1.1.1.3 Random Routing An obvious approach between the two extremes previously discussed is to select a transfer probability between 0 and 1 to forward messages at each contact. The repli- cation factor can also be a probability between 0 (none) and 1 (all). For our random protocol, we use a simple replication strategy that makes no replicas. The message is transferred every time the transfer probability is greater than the threshold. The message has some chance of being transferred to a highly mobile node and thus may have a better chance to reach its destination before the message expires. 1.1.1.4 PRoPHET Protocol PRoPHET [19] is the Probabilistic Routing Protocol using History of past Encounters and Transitivity, which is used to estimate each node’s delivery prob- ability for each other node. When node i meets node j, the delivery probability of node i for j is updated by ij ij ij p p p p ʹ = − + ( ) 1 , 0 (1.1)
- 22. Routing in MobileOpportunistic Networks ◾ 5 © 2011 by Taylor & Francis Group, LLC where p0 is an initial probability, a design parameter for a given network. Lindgren et al. [19] chose 0.75, as did we in our evaluation. When node i does not meet j for some time, the delivery probability decreases by ʹ = p p ij k ij α , (1.2) where α is the aging factor (α < 1), and k is the number of time units since the last update. The PRoPHET protocol exchanges index messages as well as delivery probabili- ties. When node i receives node j’s delivery probabilities, node i may compute the transitive delivery probability through j to z with ʹ = + − p p p p p iz iz iz ij jz ( ) 1 β, (1.3) where β is a design parameter for the impact of transitivity; we use β = 0.25 (as in [19]). ZebraNet [13] used a simple history-based routing protocol, which calculates the probabilitysimilartoEquation(1.2)toestimatetheprobabilitythatanodecancommu- nicate with the destination, the base station. Only one base station exists in ZebraNet. 1.1.1.5 Link-State Protocol Su et al. [23] use a link-state approach to estimate the weight of each path from the source of a message to the destination. They use the median intercontact duration or exponentially aged intercontact duration as the weight on links. The exponen- tially aged intercontact duration of node i and j is computed by ʹ = + − − w w t t ij ij ij α α ( )( ) 1 , (1.4) where t is the current time, tij is the time of last contact, and α is the aging factor. At the first contact, we just record the contact time. Nodes share their link-state weights when they can communicate with each other, and messages are forwarded to the neighbor that has the path to destination with the lowest link-state weight. 1.1.2 Timely Contact Probability We, too, use historical contact information to estimate the probability of meeting other nodes in the future. But our method differs in that we estimate the contact probability within a period of time. For example, what is the contact probability in the next hour? Neither PRoPHET nor Link-State considers time in this way. One way to estimate the timely contact probability is to use the ratio of the total contact duration to the total time. However, this approach does not capture the frequency of contacts. For example, one node may have a long contact with
- 23. 6 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC another node, followed by a long noncontact period. A third node may have a short contact with the first node, followed by a short noncontact period. Using the above estimation approach, both examples would have similar contact probability. In the second example, however, the two nodes have more frequent contacts. We design a method to capture the contact frequency of mobile nodes. For this purpose, we assume that even short contacts are sufficient to exchange messages.* The probability for node i to meet node j is computed by the following proce- dure. We divide the contact history Hij into a sequence of n periods of ΔT starting from the start time (t0) of the first contact in history Hij to the current time. We number each of the n periods from 0 to n – 1, then check each period. If node i had any contact with node j during a given period m, which is [t0 + mΔT,t0 + (m + 1) ΔT), we set the contact status Im to be 1; otherwise, the contact status Im is 0. The probability pij ( ) 0 that node i meets node j in the next ΔT can be estimated as the average of the contact status in prior intervals: p n I ij m n m ( ) 0 0 1 1 = . = − ∑ (1.5) To adapt to the change of contact patterns, and reduce the storage space for contact histories, a node may discard old contacts from the history; in this situa- tion, the estimate would be based on only the retained history. The above probability is the direct contact probability of two nodes. We are also interested in the probability that we may be able to pass a message through a sequence of k nodes. Therefore, we need not only use the node with highest contact probability, but also several other nodes. With all nodes’ contact probabilities, we can compute the k-order probability. Assuming nodes’ contact events are indepen- dent, we define the k-order probability inductively, p p p p ij k ij r ir rj k ( ) ( ) ( ) ( ) = + ∑ − 0 0 1 , (1.6) where r is any node other than i or j. Since node contact events may not be entirely independent, we recognize that Equation (1.5) only estimates an approximate prob- ability. Indeed, all of the prediction-based methods use heuristic approximations and incomplete data, given the nature of this routing problem. 1.1.3 Our Routing Protocol We first consider the case of a two-hop path—that is, with only one relay node. We consider two approaches: either the receiving neighbor decides whether to act as a relay, or the source decides which neighbors to use as relays. * In our simulation, however, we accurately model the communication costs and some short contacts will not succeed in the transfer of all messages.
- 24. Routing in MobileOpportunistic Networks ◾ 7 © 2011 by Taylor & Francis Group, LLC 1.1.3.1 Receiver Decision Whenever a node meets other nodes, they exchange all their messages (or, as above, index messages). If the destination of a message is the receiver itself, the message is delivered. Otherwise, if the probability of delivering the message to its destination through this receiver node within ΔT is greater than or equal to a certain threshold, the message is stored in the receiver’s storage to forward to the destination. If the probability is less than the threshold, the receiver discards the message. Notice that our protocol replicates the message whenever a good relay comes along. 1.1.3.2 Sender Decision To make decisions, a sender must have the information about its neighbors’ contact probability with a message’s destination. Therefore, meta-data exchange is necessary. When two nodes meet, they exchange a meta-message, containing an unor- dered list of node IDs for which the sender of the meta-message has a contact prob- ability greater than the threshold. After receiving a meta-message, a node checks whether it has any message that is destined to its neighbor or to a node in the node list of the neighbor’s meta- message. If it has, it sends a copy of the message. When a node receives a message, if the destination of the message is the receiver itself, the message is delivered. Otherwise, the message is stored in the receiver’s storage for forwarding to the destination. 1.1.3.3 Multinode Relay When we use more than two hops to relay a message, each node needs to know the contact probabilities along all possible paths to the message destination. Every node keeps a contact probability matrix in which each cell pij is a con- tact probability between two nodes i and j. Each node i computes its own contact probabilities (row i) using Equation (1.5) whenever the node ends a contact with other nodes. Each row of the contact probability matrix has a version number; the version number for row i is increased only when node i updates the matrix entries in row i. Other matrix entries are updated through exchange with other nodes when they meet. When two nodes i and j meet, they first exchange their contact probability matrices. Node i compares its own contact matrix with node j’s matrix. If node j’s matrix has a row l with a higher version number, then node i replaces its own row l with node j’s row l. Likewise, node j updates its matrix. After the exchange, the two nodes will have identical contact probability matrices. Next, if a node has a message to forward, the node estimates its neighboring node’s order-k contact probability to contact the destination of the message using Equation (1.6). The order k is a design factor for the multinode relay protocols. If
- 25. 8 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC pij (m) for any 0 < m < k, is above a threshold, or if j is the destination of the message, node i will send a copy of the message to node j. All the previous effort serves to determine the transfer probability when two nodes meet. The replication decision is orthogonal to the transfer decision. In our implementation, we always replicate. Although PRoPHET [19] and Link-State [23] do no replication, as described, we added replication to both protocols for better comparison to our protocol. 1.1.4 Evaluation Results We evaluate and compare the results of direct delivery, epidemic, random, PRoPHET, Link-State, and timely contact routing protocols. 1.1.4.1 Mobility Traces We use real mobility data collected at Dartmouth College. Dartmouth College has collected association and disassociation messages from devices on its wire- less network since spring 2001 [15]. Each message records the wireless card MAC address, the time of association and disassociation, and the name of the access point (AP). We treat each unique MAC address as a node. For more information about Dartmouth’s network and the data collection, see previous studies [8,14]. Our data are not contacts in a mobile ad hoc network. We can approximate contact traces by assuming that two users can communicate with each other when- ever they are associated with the same access point. Chaintreau et al. [3] used Dartmouth data traces and made the same assumption to theoretically analyze the impact of human mobility on opportunistic forwarding algorithms. This assump- tion may not be accurate,* but it is a good first approximation. In our simulation, we imagine the same clients and same mobility in a network with no access points. Since our campus has full Wi-Fi coverage, we assume that the location of access points had little impact on users’ mobility. We simulated one full month of trace data (November 2003), with 5,142 users. Although prediction-based protocols require prior contact history to estimate each node’s delivery probability, our preliminary results show that the performance improvement of warming-up over one month of trace was marginal. Therefore, for simplicity, we show the results of all protocols without warm-up. * Two nodes may not have been able to directly communicate while they were at far sides of an access point, or two nodes may have been able to directly communicate if they were between two adjacent access points.
- 26. Routing in MobileOpportunistic Networks ◾ 9 © 2011 by Taylor & Francis Group, LLC 1.1.4.2 Simulator We developed a custom simulator.* Since we used contact traces derived from real mobility data, we did not need a mobility model and omitted physical and link-layer details for node discovery. We are aware that the time for neighbor discovery in different wireless technologies varies from less than one second to several seconds. Furthermore, connection establishment also takes time, such as Dynamic Host Configuration Protocol (DHCP). In our simulation, we assumed that the nodes could discover and connect to each other instantly when they were associated with the same AP. To accurately model communication costs, how- ever, we simulated some MAC-layer behaviors, such as collision. The default settings of the network of our simulator are listed in Table 1.1, using the values recommended by other papers [23,19]. The message probability was the probability of generating messages, as described below in Section 1.1.4.3. The default transmission bandwidth was 11 Mb/s. When one node tried to transmit a message, it first checked whether another node was transmitting. If it was, the node backed off for a random number of slots. Each slot was 1 millisecond, and the maximum number of back-off slots was 30. The size of messages was uniformly distributed between 80 bytes and 1024 bytes. The hop count limit (HCL) was the maximum number of hops before a message should stop forwarding. The time to live (TTL) was the maximum duration that a message may exist before expir- ing. The storage capacity was the maximum space that a node can use for storing messages. For our routing method, we used a default prediction window ΔT of 10 hours and a probability threshold of 0.01. The replication factor r was not limited by default, so the source of a message transferred the messages to any other node that had a contact probability with the message destination higher than the prob- ability threshold. All protocols (except direct and random) used the index-message optimization method above. 1.1.4.3 Message Generation After each contact event in the contact trace, we generated a message with a given probability; we chose a source node and a destination node randomly using a uni- form distribution across nodes seen in the contact trace up to the current time. When there were more contacts during a certain period, there was a higher like- lihood that a new message was generated in that period. This correlation is not * We tried to use a general network simulator (ns2), which was extremely slow when simulating a large number of mobile nodes (in our case, more than 5000 nodes) and provided unnecessary detail in modeling lower-level network protocols.
- 27. 10 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC unreasonable, since there were more movements and contacts during the day than during the night. Figure 1.1 shows the statistics of the numbers of movements and the numbers of contacts during each hour. These statistics were accumulated across all users through the whole month. The plot shows a clear diurnal activity pattern; the activities were lowest around 5 a.m. and peaked between 4 p.m. and 5 p.m. We assume that in some applications, network traffic exhibits similar patterns; that is, people send more messages during the day, too. 1.1.4.4 Metrics We define a set of metrics that we used in evaluating routing protocols in oppor- tunistic networks: ◾ ◾ Delivery ratio, the ratio of the number of messages delivered to the number of total messages generated. ◾ ◾ Delay, the duration between a message’s generation time and the message’s delivery time. ◾ ◾ Message transmissions, the total number of messages transmitted during the simulation across all nodes. ◾ ◾ Meta-data transmissions, the total number of meta-data units transmitted during the simulation across all nodes. 0 20000 40000 60000 80000 100000 120000 0 5 10 15 20 Number of Occurrences Hour Movements Contacts Figure 1.1 Movements and contacts during each hour.
- 28. Routing in MobileOpportunistic Networks ◾ 11 © 2011 by Taylor & Francis Group, LLC ◾ ◾ Message duplications, the number of times a message copy occurred. ◾ ◾ Storage usage, the max and mean of maximum storage (bytes) used across all nodes. 1.1.4.5 Results Here we compare our simulation results of the six routing protocols. Figure 1.2 shows the delivery ratio of all the protocols, with different TTLs. (In all the plots in this section, prediction stands for our method, state stands for the Link-State protocol, and prophet represents PRoPHET.) Although we had 5142 users in the network, the direct-delivery and random protocols had low delivery ratios (note the log scale). Even for messages with an unlimited lifetime, only 59 out of 2077 messages were delivered during this one-month simulation. The delivery ratio of epidemic routing was the best. The three prediction-based routing schemes had low delivery ratios, compared with epidemic routing. Although our method was slightly better than the other two, the advantage was marginal. Note that with a 10-hour TTL, the three prediction-based routing protocols had only about 4% messages delivered. This low delivery ratio limits the applicability of these routing protocols in practice. The high delivery ratio of epidemic routing came with a price: excessive trans- missions. Figure 1.3 shows the number of message data transmissions. The number 0.001 0.01 0.1 1 Unlimited 100 24 10 1 Delivery Ratio Message Time-to-live (TTL) (hours) Direct Random Prediction State Prophet Epidemic Figure 1.2 Delivery ratio (log scale). The direct and random protocols for one- hour TTL had delivery ratios that were too low to be shown in the plot.
- 29. 12 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC of message transmissions in epidemic routing was more than 10 times higher than for the prediction-based routing protocols. Obviously, the direct delivery protocol had the lowest number of message transmissions—the number of messages deliv- ered. Among the three prediction-based methods, PRoPHET transmitted fewer messages, but all three had comparable delivery ratios, as seen in Figure 1.2. Figure 1.4 shows that epidemic and all prediction-based methods had substantial meta-data transmissions, though epidemic routing had relatively more (at least for shorter TTLs). Because the epidemic protocol transmitted messages at every contact, in turn, more nodes had messages that required meta-data transmission during con- tact. The direct-delivery and random protocols had no meta-data transmissions. In addition to its message transmissions and meta-data transmissions, the epi- demic routing protocol also had excessive message duplications, spreading replicas of messages over the network. Figure 1.5 shows that epidemic routing had one or two orders of magnitude more duplication than the prediction-based protocols. Recall that the direct-delivery and random protocols did not replicate, and thus had no data duplications. Figure 1.6 shows the median delivery delays, and Figure 1.7 shows the mean delivery delays. All protocols show similar delivery delays in both mean and median measures for medium TTLs but differ for long and short TTLs. With a 100-hour TTL, or unlimited TTL, epidemic routing had the shortest delays. Direct delivery had the longest delay for unlimited TTL, but it had the shortest delay for the one- hour TTL. 1 10 100 1000 10000 100000 1e+06 1e+07 1e+08 Unlimited 100 24 10 1 Number of Messages Transmitted Message Time-to-live (TTL) (hours) Direct Random Prediction State Prophet Epidemic Figure 1.3 Message transmissions (log scale).
- 30. Routing in MobileOpportunistic Networks ◾ 13 © 2011 by Taylor & Francis Group, LLC Direct Random Prediction State Prophet Epidemic 1 10 100 1000 10000 100000 1e+06 1e+07 1e+08 Unlimited 100 24 10 1 Number of Meta-data Transmissions Message Time-to-live (TTL) (hours) Figure 1.4 Meta-data transmissions (log scale). Direct and random protocols had no meta-data transmissions. 1 10 100 1000 10000 100000 1e+06 1e+07 1e+08 Unlimited 100 24 10 1 Number of Message Duplications Message Time-to-live (TTL) (hours) Direct Random Prediction State Prophet Epidemic Figure 1.5 Message duplications (log scale). Direct and random protocols had no message duplications.
- 31. 14 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC 1 10 100 1000 10000 Delay (minutes) Unlimited 100 24 10 1 Message Time-to-live (TTL) (hours) Direct Random Prediction State Prophet Epidemic Figure 1.6 Median delivery delay (log scale). 1 10 100 1000 10000 Delay (minutes) Unlimited 100 24 10 1 Message Time-to-live (TTL) (hours) Direct Random Prediction State Prophet Epidemic Figure 1.7 Mean delivery delay (log scale).
- 32. Routing in MobileOpportunistic Networks ◾ 15 © 2011 by Taylor & Francis Group, LLC The results seem contrary to our intuition: the epidemic routing protocol should be the fastest routing protocol since it spreads messages all over the network. Indeed, the figures show only the delay time for delivered messages. For direct deliv- ery, random, and the probability-based routing protocols, relatively few messages were delivered for short TTLs, so many messages expired before they could reach their destination. Those messages had infinite delivery delay and were not included in the median or mean measurements. For longer TTLs, more messages were deliv- ered even for the direct-delivery protocol. The statistics of longer TTLs for com- parison are more meaningful than those of short TTLs. Since our message generation rate was low, the storage usage was also low in our simulation. Figure 1.8 and Figure 1.9 show the maximum and average of maxi- mum volume (in kb) of messages stored in each node. The epidemic routing had the most storage usage. The message time-to-live parameter was the big factor affecting the storage usage for epidemic and prediction-based routing protocols. We studied the impact of different parameters of our prediction-based routing protocol. Our prediction-based protocol was sensitive to several parameters, such as the probability threshold. Figure 1.10 shows the delivery ratios when we used different probability thresholds. (The leftmost value, 0.01, is the value used for the other plots.) A higher probability threshold limited the transfer probability, so fewer messages were delivered. We also had fewer transmissions, as shown in Figure 1.11. With a larger prediction window ΔT, we got higher contact probability. Thus, for the same probability threshold, we had a higher delivery ratio (Figure 1.12), and 1 10 100 1000 10000 Storage Usage (KB) Unlimited 100 24 10 1 Message Time-to-live (TTL) (hours) Direct Random Prediction State Prophet Epidemic Figure 1.8 Max of maximum storage usage across all nodes (log scale).
- 33. 16 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC 0.1 1 Storage Usage (KB) Direct Random Prediction State Prophet Epidemic 10 100 1000 10000 Unlimited 100 24 10 1 Message Time-to-live (TTL) (hours) Figure 1.9 Mean of maximum storage usage across all nodes (log scale). 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 Delivery Ratio Probability Threshold Figure 1.10 Probability threshold impact on delivery ratio of timely contact routing. We used threshold 0.01 for other plots.
- 34. Routing in MobileOpportunistic Networks ◾ 17 © 2011 by Taylor & Francis Group, LLC 0 0.5 1 1.5 2 2.5 3 3.5 0 0.2 0.4 0.6 0.8 1 Number of Messages Transmitted (million) Probability Threshold Figure 1.11 Probability threshold impact on message transmission of timely con- tact routing. We used threshold 0.01 for other plots. 0 0.2 0.4 0.6 0.8 1 0.01 0.1 1 10 100 Delivery Ratio Prediction Window (hours) Figure 1.12 Prediction window impact on delivery ratio of timely contact rout- ing (semi-log scale). We used prediction window ΔT = 10 hours for other plots.
- 35. 18 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC more transmissions (Figure 1.13). Our protocol was not as sensitive to the pre- diction window as it was to probability threshold. When the prediction window increased to one hour or longer, the delivery ratio and the number of messages transmitted increased only slightly. Therefore, the contact probability within one hour or longer did not change much. 1.1.5 Related Work Fall [6] presents an overview of DTNs. It gives examples of delay-tolerant networks: terrestrial mobile networks, exotic media networks (e.g., satellite, deep space), mili- tary ad-hoc networks, and sensor networks. The challenges of those networks are high latency, disconnection, and long queuing time. Fall focuses on the interoper- ability of heterogeneous networks (e.g., Internet, satellite networks, Intranet, or ad-hoc networks). The author proposes to use a DTN gateway to connect different networks, and defines naming of network entities. Chuah et al. [4] extends the naming convention in Fall’s DTN architecture framework [6] to further divide a network region into groups. This work also discusses details of neighbor discovery, gateway selection, mobility management, and route discovery. Jain et al. [12] later extend Fall’s framework [6]. They propose and evaluate sev- eral routing algorithms in two example scenarios: remote village and city bus. Both scenarios have predictable connectivity. The remote village has a dial-up connection 0 0.5 1 1.5 2 2.5 3 3.5 0.01 0.1 1 10 100 Number of Messages Transmitted (million) Prediction Window (hours) Figure 1.13 Prediction window impact on message transmission of timely con- tact routing. We used prediction window ΔT = 10 hours for other plots.
- 36. Routing in MobileOpportunistic Networks ◾ 19 © 2011 by Taylor & Francis Group, LLC late at night, satellite connection every few hours, and a motorbike message courier every 4 hours. The city buses follow bus routes. Five routing algorithms are evalu- ated in the paper: ◾ ◾ First Contact (FC): a message is forwarded to one random current contact or to the first available contact. ◾ ◾ Minimum Expected Delay (MED): use Dijkstra’s algorithm to compute the cost (delay) of each path and choose an edge that leads to the path that has the least sum of the average waiting time, propagation delay, and transmission delay. ◾ ◾ Earliest Delivery (ED): use modified Dijkstra with time varying cost, but without queue waiting time. ◾ ◾ Earliest Delivery with Local Queue (EDLQ): ED with the cost function incorporating local queuing. ◾ ◾ Earliest Delivery with All Queue (EDAQ): ED with the cost function incor- porating all nodes’ queuing info. ◾ ◾ Linear Program (LP): use all the contacts, queuing, and traffic information. Table 1.1 Default Settings of the Opportunistic Network Simulation Parameter Default Value message probability 0.001 bandwidth 11 Mb/s transmission slot 1 millisecond max back-off slots 30 message size 80–1024 bytes hop count limit (HCL) unlimited time to live (TTL) unlimited storage capacity unlimited predictions window ΔT 10 hours probability threshold 0.01 contact history length 20 replication always aging factor α 0.9 (0.98 PRoPHET) initial probability p0 0.75 (PRoPHET) transitivity impact β 0.25 (PRoPHET)
- 37. 20 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC They conclude that in networks with limited resources, the smarter algorithms (ED, EDLQ, and EDAQ) may provide a significant benefit. They also found that global knowledge may not be required for good performance, since EDLQ performed as well as EDAQ in many cases. The routing problem, however, when the contacts are predict- able, is relatively simple, especially in the remote village scenario, where the village com- municates with only the city through three different routes. The LP algorithm provides only a theoretical analysis. In practice, the required information is not available. Li and Rus [18] propose algorithms to guide mobile nodes’ movements for com- munication in disconnected mobile ad hoc networks. Two algorithms were studied. The first assumes that mobilities and locations are known to all nodes. The second one is more generalized and does not assume this knowledge. Li and Rus describe a network situation in which nodes are moving with their tasks and may move to other nodes for message delivery. The proposed algorithms avoid traditional wait- ing and retry schemes. The big disadvantage is that the algorithms require users to move based on the needs of messages. This means that users (people) need to be aware of the messages and decide if relay is necessary. The algorithms are tools to aid the user to make the movement decision. Wang and Wu [26] studied two basic routing approaches (direct delivery and flooding) and propose a scheme based on delivery probability. They found that their delivery-probability scheme achieves a higher delivery ratio than either of the basic routing approaches. They also studied the average delay and transmission overhead for all three delivery methods. Although the flooding approach has the lowest average delay, the delivery ratio suffers because excessive message duplica- tions exhaust storage buffers. The authors discuss a mobile sensor network in which all sensor nodes transmit messages to sink nodes. Messages can be delivered to any sink node. The limited number of destinations enables the simple probability esti- mation of the proposed scheme. LeBrun et al. [16] propose a location-based, delay-tolerant network routing protocol. Their algorithm assumes that every node knows its own position, and the single destination is stationary at a known location. A node forwards data to a neighbor only if the neighbor is closer to the destination than its own position. Our protocol does not require knowledge of the nodes’ locations, and it learns their contact patterns. Leguay et al. [17] use a high-dimensional space to represent a mobility pattern, then route messages to nodes that are closer to the destination node in the mobility pattern space. Node locations are required to construct mobility patterns. Musolesi et al. [20] propose an adaptive routing protocol for intermittently con- nected mobile ad hoc networks. They use a Kalman filter to compute the prob- ability that a node delivers messages. This protocol assumes group mobility and cloud connectivity; that is, nodes move as a group, and among this group of nodes a contemporaneous end-to-end connection exists for every pair of nodes. When two nodes are in the same connected cloud, destination-sequenced distance-vector (DSDV) [21] routing is used.
- 38. Routing in MobileOpportunistic Networks ◾ 21 © 2011 by Taylor & Francis Group, LLC Erasure coding [11,25] explores coding algorithms to reduce message replicas. The source node replicates a message m times, then uses a coding scheme to encode them in one big message. After replicas are encoded, the source divides the big message into k blocks of the same size and transmits a block to each of the first k encountered nodes. If m of the blocks are received at the destination, the mes- sage can be restored, where m < k. In a uniformly distributed mobility scenario, the delivery probability increases because the probability that the destination node meets m relays is greater than it meets k relays, given m < k. Island Hopping [22] considers a network topology that consists of nodes of a set of connected subgraphs, or connectivity islands, and a set of edges representing possible node movements between those islands. Nodes learn the entire graph by exchanging their views of the network based on prior node movement. We did not implement and evaluate these routing protocols because either they require unrealistic future information [12], controllable mobile nodes [18], or domain-specific information (location information) [16,17]; they assume certain mobility patterns [20,22]; or they present orthogonal approaches [11,25] to other routing protocols. A recent study by Conan, Leguay, and Friedman [5] is similar to our work. They use the intercontact time to calculate the expected delivery time. Their relay strategy is based on the minimum expected delivery time. The difference from our work is that our relay strategy is based on the maximization of the contact probability within a given time interval. They also used the Dartmouth data, as well as two other data sets for their simulation. They constructed a subset of the Dartmouth data set, in which all users appear on the network every day. Therefore, their Dartmouth data simulation results have higher delivery ratios and shorter deliver delays than ours. More recently, Yuan et al. [27] propose Predict and Relay, which uses a time- homogeneous semi-Markov process model to predict the future contacts of two specified nodes at a specified time. With this model, a node estimates the future contacts of its neighbors and the destination, and then selects a proper neighbor as the next hop to forward the message. A synthetic mobility model is used for their simulation. Nodes move among a set of landmark locations with a given prob- ability. It is difficult to compare our work with theirs because they use a different mobility model. 1.1.6 Summary We simulated and evaluated several routing protocols in opportunistic networks. We propose a prediction-based routing protocol for opportunistic networks. We evaluate the performance of our protocol using realistic contact traces and compare to five existing routing protocols: three simple protocols and two other prediction- based routing protocols. Our simulation results show that direct delivery had the lowest delivery ratio, the fewest data transmissions, and no meta-data transmission or data duplication.
- 39. 22 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC Direct delivery is suitable for devices that require extremely low power consump- tion. The random protocol increased the chance of delivery for messages otherwise stuck at some low-mobility nodes. Epidemic routing delivered the most messages. The excessive transmissions and data duplication, however, consume more resources than portable devices may be able to provide. Direct-delivery, random, and epidemic routing protocols are not practical for real deployment of opportunistic networks because they either had an extremely low delivery ratio or had an extremely high resource consumption. The prediction- based routing protocols had a delivery ratio more than 10 times better than that for direct-delivery and random routing, and they had fewer transmissions and used less storage than epidemic routing. They also had fewer data duplications than epidemic routing. All the prediction-based routing protocols that we evaluated had similar per- formance. Our method had a slightly higher delivery ratio but more transmissions and higher storage usage. There are many parameters for prediction-based routing protocols, however, and different parameters may produce different results. Indeed, there is an opportunity for some adaptation; for example, high-priority messages may be given higher transfer and replication probabilities to increase the chance of delivery and reduce the delay, or a node with infrequent contact may choose to raise its transfer probability. We must note that our evaluations were based solely on the Dartmouth traces. Our findings and conclusions may or may not apply to other network environments, because users in different network environments may have distinct mobility pat- terns and thus distinct handoff patterns. We also note that our traces were not motion records, our contact model was based on association records, and messages were synthetically generated. We believe, however, that our traces are a good match for the evaluation of handoff predictions and bandwidth reservations. A more pre- cise evaluation may need motion traces—that is, the physical location of users and models to determine users’ connectivity. References [1] John Burgess, Brian Gallagher, David Jensen, and Brian Neil Levine. MaxProp: Routing for vehicle-based disruption-tolerant networks. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), April 2006. [2] Tracy Camp, Jeff Boleng, and Vanessa Davies. A survey of mobility models for ad hoc network research. Wireless Communication & Mobile Computing (WCMC): Special Issue on Mobile Ad Hoc Networking: Research, Trends and Applications, 2(5):483–502, 2002. [3] Augustin Chaintreau, Pan Hui, Jon Crowcroft, Christophe Diot, Richard Gass, and James Scott. Impact of human mobility on the design of opportunistic forwarding algorithms. In Proceedings of the IEEE International Conference on Computer Com munications (INFOCOM), April 2006.
- 40. Routing in MobileOpportunistic Networks ◾ 23 © 2011 by Taylor & Francis Group, LLC [4] Mooi Choo Chuah, Liang Cheng, and Brian D. Davison. Enhanced disruption and fault tolerant network architecture for bundle delivery (EDIFY). In Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), 2005. [5] Vania Conan, Jeremie Leguay, and Timur Friedman. Fixed point opportunistic routing in delay tolerant networks. IEEE Journal on Selected Areas in Communications (JSAC), 26(5):773–782, June 2008. [6] Kevin Fall. A delay-tolerant network architecture for challenged Internets. In Proceed ings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (ACM SIGCOMM), pp. 27–34, August 2003. [7] Khaled A. Harras and Kevin C. Almeroth. Inter-regional messenger scheduling in delay tolerant mobile networks. In Proceedings of IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks (WoWMoM), pp. 93–102, June 2006. [8] Tristan Henderson, David Kotz, and Ilya Abyzov. The changing usage of a mature campus- wide wireless network. In Proceedings of the Annual International Conference on Mobile Computing and Networking (ACM Mobicom), pp. 187–201. ACM Press, September 2004. [9] Pan Hui, Augustin Chaintreau, James Scott, Richard Gass, Jon Crowcroft, and Christophe Diot. Pocket switched networks and human mobility in conference envi ronments. In Proceedings of ACM SIGCOMM Workshop on Delay Tolerant Networking and Related Networks (WDTN), pp. 244–251, August 2005. [10] Ravi Jain, Dan Lelescu, and Mahadevan Balakrishnan. Model T: An empirical model for user registration patterns in a campus wireless LAN. In Proceedings of the Annual International Conference on Mobile Computing and Networking (ACM Mobicom), pp. 170–184, 2005. [11] Sushant Jain, Mike Demmer, Rabin Patra, and Kevin Fall. Using redundancy to cope with failures in a delay tolerant network. In Proceedings of the Conference on Applica tions, Technologies, Architectures, and Protocols for Computer Communications (ACM SIGCOMM), pp. 109–120, August 2005. [12] Sushant Jain, Kevin Fall, and Rabin Patra. Routing in a delay tolerant network. In Pro ceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (ACM SIGCOMM), pp. 145–158, August 2004. [13] Philo Juang, Hidekazu Oki, Yong Wang, Margaret Martonosi, Li-Shiuan Peh, and Daniel Rubenstein. Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with ZebraNet. In TheTenth International Conference on Ar chitectural Support for Programming Languages and Operating Systems, pp. 96–107, October 2002. [14] David Kotz and Kobby Essien. Analysis of a campus-wide wireless network. Wireless Networks, 11:115–133, 2005. [15] David Kotz, Tristan Henderson, and Ilya Abyzov. CRAWDAD data set dart-mouth/ campus. http://crawdad. cs. dartmouth.edu/dartmouth/campus, December 2004. [16] Jason LeBrun, Chen-Nee Chuah, Dipak Ghosal, and Michael Zhang. Knowledge- based opportunistic forwarding in vehicular wireless ad hoc networks. In Proceedings of IEEE Vehicular Technology Conference (VTC), pp. 2289–2293, May 2005. [17] Jeremie Leguay, Timur Friedman, and Vania Conan. Evaluating mobility pattern space routing for DTNs. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), April 2006. [18] Qun Li and Daniela Rus. Communication in disconnected ad-hoc networks using mes sage relay. Journal of Parallel and Distributed Computing, 63(1):75–86, January 2003.
- 41. 24 ◾ LiboSong and David F. Kotz © 2011 by Taylor & Francis Group, LLC [19] Anders Lindgren, Avri Doria, and Olov Schelen. Probabilistic routing in intermittently connected networks. In Workshop on Service Assurance with Partial and Intermittent Resources (SAPIR), pp. 239–254, 2004. [20] Mirco Musolesi, Stephen Hailes, and Cecilia Mascolo. Adaptive routing for intermit tently connected mobile ad hoc networks. In Proceedings of IEEE International Sym posium on a World of Wireless Mobile and Multimedia Networks (WoWMoM), pp. 183–189, June 2005. Extended version. [21] C. E. Perkins and P. Bhagwat. Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers. Computer Communication Review, pp. 234– 244, October 1994. [22] Natasa Sarafijanovic-Djukic, Michal Piorkowski, and Matthias Grossglauser. Island hop ping: Efficient mobility-assisted forwarding in partitioned networks. In Proceedings of IEEE Communications Society Conference on Sensor, Mesh, and Ad Hoc Communica tions and Networks (SECON), September 2006. [23] Jing Su, Ashvin Goel, and Eyal de Lara. An empirical evaluation of the student-net delay tolerant network. In Proceedings of the International Conference on Mobile and Ubiquitous Systems (MobiQuitous), July 2006. [24] Amin Vahdat and David Becker. Epidemic routing for partially-connected ad hoc net works. Technical Report CS-2000-06, Duke University, July 2000. [25] Yong Wang, Sushant Jain, Margaret Martonosi, and Kevin Fall. Erasure-coding based routing for opportunistic networks. In Proceedings of ACM SIGCOMM Workshop on Delay Tolerant Networking and Related Networks (WDTN), pp. 229–236, August 2005. [26] Yu Wang and Hongyi Wu. DFT-MSN: The delay fault tolerant mobile sensor network for pervasive information gathering. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), April 2006. [27] Quan Yuan, Ionut Cardei, and Jie Wu. Predict and relay: An efficient routing in dis- ruption-tolerant networks. In Proceedings of ACM International Symposium on Mo bile Ad Hoc Networking and Computing (MobiHoc), May 2009.
- 42. 25 © 2011 byTaylor & Francis Group, LLC Chapter 2 State of the Art in Modeling Opportunistic Networks Thabotharan Kathiravelu and Arnold Pears Uppsala University Contents 2.1 Introduction................................................................................................26 2.2 Background. ................................................................................................27 2.2.1 Trace Collection and Analysis. .........................................................27 2.2.2 Modeling Contacts..........................................................................30 2.2.3 Mobility Models..............................................................................32 2.2.4 New Generation Models..................................................................33 2.2.5 Simulation Tools for Modeling and Analysis...................................35 2.2.6 A Connectivity Model.....................................................................36 2.2.7 Application of the Connectivity Model and a Content Distribution Scenario–Based Study.................................................37 2.2.8 Related Work in Connectivity Modeling.........................................41 2.2.9 Open Problems and Challenges...................................................... 44 2.3 Chapter Summary. ......................................................................................45 References........................................................................................................... 46
- 43. 26 ◾ ThabotharanKathiravelu and Arnold Pears © 2011 by Taylor & Francis Group, LLC 2.1 Introduction Opportunistic networking explores the data transmission potential of small mobile devices, such as mobile phones and Personal Digital Assistants (PDAs). Small handheld wireless devices carried by humans form opportunistic networks and can utilize intermittent contact with other devices to exchange data [10,28]. Potential opportunistic networks arise as device users congregate and disperse [38]. For example, when people travel in a subway train or in a commuter bus they are in close proximity to other passengers and their mobile devices can contact each other to transfer information —for instance, an MP3 file. Figure 2.1 shows the typical formation of an opportunistic networking environment and how the content of interest is forwarded opportunistically. Current research in opportunistic networks ranges from opportunistic for- warding strategies, through modeling device contacts, to identifying appropriate use cases and evaluation scenarios, and developing theoretical and mathematical models. Performance modeling and analysis are of both practical and theoreti- cal importance. Since activities in opportunistic networking are still in their early stages, performance modeling is an essential ingredient of opportunistic network- ing research. Developing better methods for measuring system performance is also of great importance. Performance modeling helps to identify key challenges in both design and research methodologies, as well as to gain insight into the behavior of opportunistic networking systems. Figure 2.1 A typical example of formation of opportunistic contacts and the opportunistic forwarding of content of interest.
- 44. State of theArt in Modeling Opportunistic Networks ◾ 27 © 2011 by Taylor & Francis Group, LLC Simulation-based studies are widely used, and one of the main objectives of simu- lations is to provide support for new ideas. Simulation experiments explore the char- acteristics of opportunistic systems in a wide range of potential deployment scenarios and help developers to evaluate systems prior to deployment. Researchers have been actively studying device contact patterns, analyzing their frequency, duration, and pre- dictability in order to evaluate mechanisms for the exchange of content among peers. Modeling and performance evaluation constitute two major research activi- ties. Modeling device contacts is one direction of research, where new models that mimic pairwise device contacts in opportunistic networking environments have been proposed [34,45]. Validating the performance of opportunistic protocols and applications is another direction of research activity. This involves developing, test- ing, and validating protocols and applications and identifying factors that influence opportunistic content distribution. Intermittent connectivity between mobile nodes and the behavioral patterns of users make modeling and measuring the performance of opportunistic networks a challenging job. High-fidelity models are needed in order to establish the feasi- bility of data forwarding protocols and content distribution schemes, to predict performance boundaries for opportunistic applications as well as to characterize the power and memory behavior of the network, transport, and application protocols. A significant challenge in the simulation of opportunistic networks is modeling the underlying pairwise contacts between nodes. Ideally, simulations should closely emulate the behavior of “real” networks. In the remainder of this chapter we provide an overview of the state of the art in modeling opportunistic network connection structures and pairwise connectiv- ity. We summarize work in analyzing pairwise contacts in collected opportunistic connectivity traces and their findings. We then describe the role of mobility models in modeling contacts in the Mobile Ad hoc Networking research community and argue that new models are needed for opportunistic network research. We introduce connectivity models as one feasible approach to modeling contact in opportunistic networks. The scope of the approach is illustrated using a case study that explores the impact of variation in connectivity properties of the underlying network on an application that distributes content to participants in the network. 2.2 Background 2.2.1 Trace Collection and Analysis Collecting interdevice contact traces has gained much attention in Mobile Ad hoc Networks (MANET) and opportunistic networking research [10,41]. The main purpose of trace collection is to characterize interdevice contact patterns. Such characterizations are then used to validate new protocols and applications. Many researchers are convinced that collected traces will reveal many interesting facts
- 45. 28 ◾ ThabotharanKathiravelu and Arnold Pears © 2011 by Taylor & Francis Group, LLC about opportunistic contacts among devices [10,39,41]. Figure 2.2 shows the prepa- ration activities prior to opportunistic contact trace collection in an academic con- ference in December 2007. In 2004, Su et al. began investigating the feasibility of opportunistic data for- warding using human connectivity traces that were collected using PDAs [58]. Pioneering work in collecting true opportunistic contact traces and analyzing them for their underlying properties and the feasibility of forwarding using opportunis- tic contacts was carried out by Chaintreau et al. in 2005 [12]. Chaintreau et al. have analyzed three publicly available traces from the University of California, San Diego (UCSD) [42], Dartmouth University [26], and the University of Toronto [58]. UCSD traces include the client-based logs of the visibility of access points for a three-month period, while the Dartmouth University traces include SNMP* logs from access points for a four-month period. The University of Toronto trace set was collected using 20 Bluetooth-enabled PDAs carried by students for a period of 16 days. In addition to these traces, Hui et al. have conducted their own experiments with iMote devices and have collected three different contact trace sets [28]. Of these three trace sets, the Intel and Cambridge traces were collected in research lab settings, whereas the iMotes were carried by researchers and doctoral students. The Infocom trace set was collected at the IEEE INFOCOM 2005 conference and the iMotes were carried by the conference participants. iMotes are a common platform for connectivity trace collection activities. Designed by Intel, they use Bluetooth wireless technology to log their device * Simple Network Management Protocol. Figure 2.2 Small mobile devices with Bluetooth wireless connectivity are being prepared for trace collection in a conference environment in December 2007.
- 46. State of theArt in Modeling Opportunistic Networks ◾ 29 © 2011 by Taylor & Francis Group, LLC discovery and contact details with other Bluetooth-enabled devices [10,41]. Mobile phones and PDAs are also commonly used in collecting connectivity traces and are a good choice in terms of memory and battery power, but, at the same time, they are expensive to deploy on a larger scale [35]. All these collected traces were analyzed for their interdevice connection proper- ties in order to understand the constraints of opportunistic data transfer, and two new terms—contact time and inter-contact time—were defined and characterized: Contact Time is the time interval during which two mobile devices are in each others’ communication range and communicate with each other. In experiments based on opportunistic networks, contact times are often recorded and used as a measure for estimating the amount of data that could possibly be transferred. Contact times also are used to determine the pattern of underlying probabilistic distributions over time. Inter-Contact Time is the time interval measured between two consecutive con- tactswhentwomobiledevicesareincontactwitheachotherintermittently.Theinter- contact time values and their distribution over the period of time are two important pieces of information. The likelihood that a device will be encountered again in a given time period can also be determined or estimated from these values. In Figure 2.3, we characterize the nature of the contact and inter-contact times of two nodes, n1 and n2, that meet each other intermittently. Many others followed the path of Chaintreau et al. in collecting traces from dif- ferent environmental settings and have analyzed the inter-device contact patterns and their distributions. Leguay et al. [41] did an experimental study in the city of Cambridge with 54 Bluetooth-enabled iMote devices that were carried by students or fixed at popular places. Contact data was logged for a period of 13 days. The connectivity information from this experiment was then used in investigating the feasibility of a citywide content distribution network. By categorizing users with different behavioral patterns, they analyzed the effectiveness of this user population in distributing data bundles.* * Data bundle is a term commonly used in delay-tolerant networking [6,9,32] to refer to aggre- gated data. The same term has also been adopted by opportunistic networking researchers to refer to clusters of data packets [32,41]. Contact time (t2–t1) Contact time (t4–t3) Contact time (t6–t5) Time t2 Time t1 Nodes n1 & n2 n1 & n2 Intercontact time (t3–t2) Intercontact time (t5–t4) n1 & n2 n1 & n2 n1 & n2 n1 & n2 Time t4 Time t3 Time t6 Time t5 Figure 2.3 Characterization of contact and inter-contact times for two nodes n1 and n2, which meet intermittently.
- 47. 30 ◾ ThabotharanKathiravelu and Arnold Pears © 2011 by Taylor & Francis Group, LLC LeBrun et al. [39] have explored the feasibility of disseminating information using transit buses on the University of California Davis campus. Each bus is equipped with a Bluetooth content-distribution cache called BlueSpot. Any device with a Bluetooth-enabled interface can connect to these caches and download files while the bus is en route. They predict the provision of services like on-demand downloads of iTunes® music files as a future killer application. The Reality Mining project [19] at MIT* collected communication proximity, location, and activity information of 100 selected participants over a nine-month period. Each participant was given a mobile phone that had both Bluetooth and cellular network accessibility. This research looked at the mobile device interactions in many directions. In Table 2.1 we present some opportunistic contact traces that are publicly avail- able at the CRAWDAD† web site. Cambridge1 was collected by Leguay et al. [41], Intel, Cambridge2, and Infocom were collected by Chaintreau et al. [12], and BSpot1, BSpot2, and BSpot3 were collected by LeBrun et al. [39]. The Access Technology mentioned as BT in the table refers to Bluetooth wireless technology [21]. The analysis of the underlying probabilistic distributions of contact and inter- contact times of all collected traces have helped researchers in developing theoretical foundations for opportunistic forwarding algorithms and strategies [11,13]. While trace collection has been, and remains, a popular activity, traces typically have rela- tively short time periods and small populations, due to the logistic challenges associ- ated with large-scale experiments [29,40,41]. Short logging periods, lack of variation in the device population, and other statistical properties limit the usefulness of many existing traces [60]. Leguay et al. [41] describe the difficulties caused by device fail- ures due to memory overflows, drained battery power, and so on in trace collection processes. Nordström et al. [53] provide insight into the challenges in measuring human mobility and collecting connectivity traces and caution researchers about the limitations inherent in using publicly available connectivity trace sets. 2.2.2 Modeling Contacts Many research studies in MANET and opportunistic networks are dependent on simulation-based studies to test and validate new hypothesis and ideas. Modeling inter-device contacts is essential in these studies in order to tell the simulation engine how the contacts are made between simulation entities [8,31,37,44]. Researchers have so far been using synthetic mobility models and human contact traces as input for simulation based studies. Recently, there have been attempts to model contacts more accurately by refining mobility models and modeling contacts using the measured properties of human connectivity traces [36,65]. We describe * Massachusetts Institute of Technology. † Community Resource for Archiving Wireless Data at Dartmouth (CRAWDAD) http:// crawdad.cs.dartmouth.edu.
- 48. State of theArt in Modeling Opportunistic Networks ◾ 31 © 2011 by Taylor & Francis Group, LLC Table 2.1 Properties of Some Publicly Available Opportunistic Connectivity Traces Device Properties Cambridge1 Intel Cambridge2 Infocom Bspot1 BSpot2 BSpot3 Device iMote iMote iMote iMote iMote iMote iMote Access Technology BT BT BT BT BT BT BT Duration (days) 13 3 5 3 4 5 6 Granularity (seconds) 120 120 120 120 120 120 120 No. of Internal Devices 54 9 12 41 20 35 33 No. of Contacts 8545 2766 6732 28216 6131 11796 11742 No. of External Devices 11357 118 203 233 512 461 586
- 49. 32 ◾ ThabotharanKathiravelu and Arnold Pears © 2011 by Taylor & Francis Group, LLC mobility models in detail and then look at the recent extensions to these models for intermittently connected mobile networks. We conclude by discussing an alterna- tive approach, connectivity models. 2.2.3 Mobility Models Mobility models generate plausible sequences of inter-device contacts synthetically based on a set of parameters that characterize the environment. Though catego- rizing any mobility model as realistic is difficult, modeling device mobility is an essential part of any simulation study. Synthetic mobility models are often prefer- able since they allow the researcher to alter the parameters of the simulation set and reproduce simulation results easily. The random waypoint (RWP) mobility model is one of the most widely used single-entity random movement methods [4]. In RWP, nodes move in a given direction with a given speed and pause occasionally to change direction or speed. Random walk and random direction are also two widely used single-entity mobil- ity models [8,32,55]. A good survey of synthetic mobility models, excluding a few of the most recent mobility models, can be found in [8]. It has been shown [8] that traditional synthetic mobility models do not model node mobility in a manner that causes the contact and inter-contact time distribu- tions of simulated nodes to decay exponentially over time [5,57,64]. Such a behav- ior is very different from what has been observed in field tests [10]. Analysis and systematic studies of the stochastic properties of earlier models have identified flaws in modeling, and new mobility models that mimic real-world environments and related movement patterns have been proposed [27,31,36,37,46]. Jardosh et al. propose a mobility model that includes obstacles in the node path in order to mimic mobility in a more realistic environment [31]. In addition to obstacles along the path of node movement, MobiREAL [37] considers the behav- ioral changes of nodes due to the surroundings, time of the day, and so on, and uses a rule-based model to describe the movement patterns of nodes. The weighted waypoint mobility model [27] recognizes that people do not choose their waypoints randomly. It models this behavior by defining popular loca- tions in the simulation field and their related popularity weight values according to the probability of choosing these locations as the next destination. In this Markov chain–based model, the selection probability of a new destination is determined based on the current location and time. Mobility models could also be designed based on the observed statistical prop- erties from human mobility traces. The observed statistical properties can then be fed into the mobility model so that the generated interdevice connectivity resembles the same statistical properties [36,65]. Kim et al. [36] describe a method for extracting user mobility tracks from recorded Wi-Fi traces. They have examined the tracks in the Wi-Fi traces and were able to extract information such as speed, pause times, destination transition
- 50. State of theArt in Modeling Opportunistic Networks ◾ 33 © 2011 by Taylor & Francis Group, LLC probabilities, and waypoints between destinations. This information is then used in forming an empirical model that can be used to generate synthetic tracks of move- ments of nodes [36]. They have validated their model by performance comparisons between trace locations and the locations determined by users carrying both GPS and 802.11 devices. A new mobility modeling technique has emerged recently based on social net- work theory [43]. Musolesi and Mascolo devised their mobility model using human social networking concepts and human connectivity traces as the basis for the rep- resentation of human movement [46]. Another group’s mobility model, also based on the social networking theory that allows nodes to be grouped depending on their social relationships and measured network structures, called the community- based mobility model, was later proposed by Musolesi and Mascolo [44]. Karlsson et al. [32] used random waypoint and random walk mobility models [8] to model node mobility to study the performance of a receiver-driven delay- tolerant content broadcasting environment. 2.2.4 New Generation Models Recent studies on various networks, such as the Internet and biological networks, have revealed that these networks have fundamentally the same properties as social networks [1,22,48,50]. Empirical studies further reveal that these social networks contain recurring elementary interaction patterns between small groups of nodes that occur substantially more often than would be expected in random networks that are determined by Poisson distributions. These recurring interactions also carry significant information about the network’s evolution and functionality. We can also observe similar recurring interactions between nodes in time-aggregated opportunistic field connectivity traces. Please refer to Figure 2.7 for a pictorial view of clusters of node contacts observed in a typical opportunistic field trace set. The set of clusters of contacts formed by the time-aggregated contacts between pairs of nodes in a connectivity trace set is a new concept in opportunistic net- working, even though the concept of clusters is often used in network analysis and graph theory. We view the existence of clusters as follows: Suppose we take a time- aggregated opportunistic connectivity trace set. This aggregated trace set can be represented by a graph, G(V, E), with a set of vertices V representing the nodes and a set of edges, E, representing the aggregated contacts between the node pairs. The edge weights represent the aggregated contact times between pairs of vertices. A subset V′ ∀ V of the vertex set induces a subgraph G[V′] = (V′, E′) with E′ = {( u,v ) | u,v ∈ V′ }. A nested decomposition of G by removing edges is a finite sequence (V0,V1,V2,...,Vk) of subsets of subgraphs of V such that V0 = V, Vi+1 is a subgraph of Vi for i Ψ k and Vk ≠ 0. We refer to the subgraphs that arise as a result of subsequent decompositions as the set of clusters of nodes. The more edges that are removed, the more clusters are formed, which eventually results in decomposing the graph into individual nodes.
- 51. 34 ◾ ThabotharanKathiravelu and Arnold Pears © 2011 by Taylor & Francis Group, LLC There exist many open source packages, such as iGraph [18] and NetworkX [23], which can be incorporated easily into scripting languages and be used for visual- izing network structures and varying natures of clusters of contacts between nodes. Please refer to Figure 2.7 for a sample diagram generated by the iGraph [18] pack- age with the application of the clustering algorithm of Clauset et al. [15]. Many other stand-alone programs and packages are available for the manipulation of net- working traces, their properties, community identification, and visualization [52]. Two important terms need to be mentioned here: the intra-cluster edges and the inter-cluster edges. An edge (u, v) is an intra-cluster edge if both u and v belong to the same cluster—otherwise it is an inter-cluster edge. In Figure 2.7, as mentioned, one can observe the existence of node clusters, intra-cluster edges, and inter-cluster edges in a typical opportunistic contact trace set after successive removal of edges of less edge weights. We hypothesize that these cluster structures will be the backbone of the net- work for these reasons. The edges that remain in the graph are of higher weights and many of them are aggregated values of repeated contacts over the period of time. They represent the recurring nature of contacts that exist between the nodes in a diurnal fashion, and such contacts are capable of forwarding content from one node to another. In addition, ensuring that the content gets distributed to these nodes will ensure that the content gets distributed to the larger user population, since we have seen that these nodes had contacts with other nodes, too, although not as often as they do with the nodes in their own cluster. The ability to model the network at such cluster levels will enable the researcher to model the backbone of the network and the network connections. Detecting clusters in opportunistic networks allows one to extract information in a more efficient way. In larger networks, identifying the inherent cluster structures narrows down the exploration work to be done. One can use the insight from social sciences to characterize clusters. When used in the analysis of large collaboration net- works, clusters reveal the contact patterns, repeated contacts, the informal organiza- tion, and the nature of information flow through the whole system [30,49,51]. The algorithm introduced by Newman [49] for identifying communities of contacts is based on the edge betweenness. The edge betweenness measures the frac- tion of all shortest paths passing on a given edge. By removing an edge with high betweenness, one can progressively split the whole network into disconnected com- ponents. Further improvements over this algorithm enable researchers to precisely divide a network into a set of clusters [15,51]. As new network features such as resilience and cluster structures emerge, new models that can model graphs with these characteristics and their inherent prop- erties are required. This will enable researchers to model not only contacts in the network but also the substructures (such as clusters of contacts) that are present in the network. Erdös and Rényi pioneered an approach [20] based on random graphs, where each pair of vertices in the graph is connected by an edge with a given probabil- ity. Such models, which are approximated by Poisson processes, are not capable
- 52. State of theArt in Modeling Opportunistic Networks ◾ 35 © 2011 by Taylor & Francis Group, LLC of generating graphs that resemble human dynamics such as social networking and entertainment [2]. Random graphs proposed by Watts and Strogatz [63], and Albert and Barabási [1] exhibit properties like power-law distributions [16] in edge degrees, freedom from scale, and small diameter, and so on, which reflect the com- plex interaction patterns determined empirically in human dynamics. Delay-tolerant networks (DTNs) propose a store-carry-and-forward message switching approach as a viable solution to the problem of intermittent connectiv- ity. Devices store messages until they encounter another suitable device, and the devices that receive messages keep on forwarding to other devices along a path that eventually delivers data to the intended recipient. In order to achieve this, the DTN architecture introduces a protocol layer called the bundle layer on top of the region- specific lower layers of the protocol stack. This bundle layer handles aggregating data into bundles and delivering them across multiple regions [9]. Characterizing interdevice contacts in delay-tolerant networking would benefit the opportunistic networking community greatly. In a recent work, Conan et al. [17] looked at three reference DTN contact data sets and, based on the statistical analysis on these data sets for their pair-wise inter-contact times, have character- ized the heterogeneity in contact and inter-contact times. Conan et al. found that the distributions of inter-contact times are well modeled by log-normal curves for a large number of node pairs. The node movement patterns in a simulation’s coordinate space indirectly result in patterns of pairwise node contacts of varying duration. Connectivity models generate pairwise contacts in the simulation of varying durations using parameters drawn from field traces, obviating the use of a mobility model. The motivation behind this approach is that mobility models are a high-overhead approach to generating pairwise node connectivity data. Therefore, why should the temporal patterns of connectivity not be modeled directly, based on estimated parameters? Generating connectivity information directly relieves the designer of the complex- ity associated with trying to develop an appropriate model and define its parame- ters. Conducting experiments with varying numbers of user populations and device connectivity properties, and the comfort of reproducing traces, rather than con- ducting real field traces, are other advantages of this approach. 2.2.5 Simulation Tools for Modeling and Analysis Since opportunistic networking is considered as a subclass of MANET research, it has adopted the simulation and other modeling tools used by the MANET com- munity for testing and validating applications and systems. As in MANET research studies, the ease of setup, repeatability of experiments, and the ease of variation in the experimental parameters make simulation-based studies the first choice of opportunistic networking researchers in support of new hypotheses and ideas. Kathiravelu and Pears [33] used the Jist/SWANS (Java in Simulation Time/ScalableWirelessAdhocNetworkSimulator)simulator,whichwasdeveloped
- 53. 36 ◾ ThabotharanKathiravelu and Arnold Pears © 2011 by Taylor & Francis Group, LLC by Rimon Barr [3], to model and a scenario-based study of an opportunistic net- working environment in order to characterize the contact patterns between mobile nodes. In Jist/SWANS, the simulation code written in Java is compiled into a set of class files as usual and then rewritten by the bytecode rewriter into simulation code. The rewritten code is then executed by the simulation engine. Further extensions, such as run time visualization, newer mobility model implementation, and so on, have also been added to Jist/SWANS simulator [14] by researchers. SWANS, which is built on top the JiST simulator, helps researchers to simulate different wireless contact scenarios with different mobility models, such as random waypoint, ran- dom walk, and teleport mobility models [33]. The layered architecture of SWANS enables researchers to further extend it according to their needs [33]. Helgason and Jonsson [25] have described their work in customizing the OMNeT++ [61] simulator to model and simulate opportunistic network contacts. They employed two different approaches to simulating opportunistic networking. In the first approach, which is called the mobility-driven method, mobility patterns of nodes are specified in a mobility trace Þle. In the second approach, which is called the contact-driven method, the time of node contacts and their durations are specified in a contact trace file. Musolesi and Mascolo [47] also used the OMNeT++ simulator to validate the performance of a new protocol called CAR (Context- Aware Routing) for DTNs using the community-based mobility model [44,45]. In addition, many researchers develop their own simulation engines to carry out experimental studies in opportunistic networks [24,41]. Since very little informa- tion is available about these simulation tools, it is not possible to describe them in detail here. Haggle testbed is a networking architecture designed to cater to the needs of mobile users by providing seamless network connectivity and application func- tionality in highly mobile environments [56,59]. Haggle separates the application logic from transport binding so that the applications can still be fully functional in highly dynamic mobile environments [59]. Haggle takes care of data handling and communications by adapting to the best available networking environment at that time based on user preferences [59]. 2.2.6 A Connectivity Model In opportunistic networking environments, the aim is to optimize the connection opportunities, and any model that attempts to represent such an environment should consider the factors that affect the most important features of real traces: the inter- contact time and the contact time [10]. Previous analysis of opportunistic contact traces indicates the significance of these two values, and any synthetic generation process should be capable of reproducing the distributions of these two values. We propose that connectivity models should be based on the analysis of connectiv- ity patterns in real networking environments. Analysis of these traces for their stochastic properties allows us to derive probability distributions to model internode relationships
- 54. State of theArt in Modeling Opportunistic Networks ◾ 37 © 2011 by Taylor & Francis Group, LLC (the so-called small world properties of social networks) as well as the probability of a relationship resulting in two nodes being connected at a given point in time. Our connectivity model is constructed in two phases: (i) We determine the social connectedness of the node set. (ii) After the device relationship network has been determined, the frequency of connection events between two related nodes results in a connectivity trace with the desired properties. We define a connectivity model M, M K P P N R C = ( ) , , , where N is the number of nodes in the simulation. K is a set of clusters [K1..Kk], for a network with k clusters. PR(A, B), is the relationship function defining the probability that any two devices A and B are related. PC(e), is a connectivity function defining the likelihood that two nodes related by an edge e establish a connection. Here e ∈ E, the set of edges deter- mined by applying the relationship function PR to all pairs of nodes in the model. We define PR, in terms of λ, the intra-cluster relationship distribution, and 𝜙, the inter-cluster relationship distribution. P K K K R i i j ( ) A B A B A B , = , ∈ ∈ ∈ ≠ λ φ where where and and i j ⎧ ⎧ ⎨ ⎪ ⎩ ⎪ (2.1) From Equation (2.1), PR(A, B) is used to compute a set of edges E that defines a graph representing the relationships between simulation nodes. If the parameters are chosen correctly, the graph obtained by applying Equation (2.1) to all node pairs will have a cluster and internode edge density to the weighted aggregated graph of the original field trace. See Nykvist and Phanse [54] for an example of such a connection graph. 2.2.7 Application of the Connectivity Model and a Content Distribution Scenario–Based Study The scenario uses parameters gleaned from the Cambridge1 iMote connectivity traces, published in [41]. It is one of a collection of connectivity traces available from CRAWDAD and is a truly opportunistic contact trace set with a comparatively large number of contacts and devices. From the Cambridge1 data we extracted
- 55. Exploring the Varietyof Random Documents with Different Content
- 56. object: and Laurabecame the passion of his soul. The thought of leaving her destitute, of leaving her sensibility to the scorns, her beauty to the temptations of poverty, was more than he could bear, and it sometimes almost overpowered him. He was naturally inclined to indolence, and as, like all indolent people, he was the creature of habit, his spirits had suffered much from the loss of the woman who, though too heartless for a friend, and too bitter for a companion, had, for twenty years, served him as a sort of stimulus. The same force of habit, joined to her improving graces and confirming worth, made Laura daily more dear to him, and he would willingly have given his life to secure her independence and happiness. Brooding on the obscurity in which she must remain, whom he judged worthy to adorn the highest station—on the poverty which awaited her during his life—on the want to which his death must consign her,—removed from his habitual occupations, and deprived of the wholesome air, and exhilarating exercises to which he had long been accustomed, he allowed his spirits to grow daily more depressed. Along with the idea of the misfortunes which his death would bring upon his darling, the fear of death settled on his mind. The little ailments to which the sedentary are liable, he magnified into the symptoms of mortal disease; and momentary pain seemed to his fancy to foretell sudden dissolution. Montreville was fast sinking into a melancholy hypochondriac. His daughter's spirits, too, failed under continued expectation, and continued disappointment; for day after day passed on, and still Hargrave came not. Her father's dejection increased her own, and her ill-disguised depression had a similar effect on him. While, however, Captain Montreville gave way without effort to his feelings, the more vigorous mind of Laura struggled to suppress the sorrow which she saw was contagious. She sometimes prevailed upon her father to seek amusement abroad, sometimes endeavoured to amuse him at home. She read to him, sung to him, exerted all her conversation talent to entertain him; and often, when all was in vain, when he would answer her by forced smiles, languid gestures, or
- 57. heavy sighs, shewould turn aside to wipe the tears from her eyes, then smile, and attempt her task again. In these labours she had now, it is true, the assistance of an intelligent companion. De Courcy came often; and the Captain seemed to receive a pleasure from his visits, which even Laura's efforts could not bestow. The tenderness of his child, indeed, appeared sometimes to overpower him; for, when she was exerting herself to divert his melancholy, he would gaze upon her for a while in an agony of fondness, then suddenly desire to be left alone, and dismiss her from his presence. But De Courcy's attentions seemed always welcome. He soothed the irritated mind with respectful assiduities—he felt for its sickly sensibility—and, though ignorant of the cause of Montreville's dejection, found in alleviating it a pleasure, which was more than doubled by the undisguised approbation and gratitude of Laura. His sister, too, came to visit Miss Montreville, and, apologizing for her mother, who was unable to accompany her, brought an invitation for the Captain and his daughter to dine in Audley Street. Laura, in hopes of amusing her father, prevailed on him to accept the invitation; and an early day was fixed for the visit. She was pleased with the frankness and gaiety of Harriet's manner, and her curiosity was roused by Captain Montreville's praises of Mrs De Courcy. The day arrived, and Laura prepared to accompany her father, not without trepidation at the thought of entering, for the first time in her life, a room which she expected to find full of strangers. When she had finished dressing, he examined her with triumph; and thought that nothing in nature was so perfect. The thought was legible in his countenance, and Laura, with great simplicity, answered to it as if it had been spoken. 'Except to please you,' said she, 'I wish I had been neither tall nor pretty, for then I should have been allowed to move about without notice.' 'Then, too,' thought she with a heavy sigh, 'I should have been loved for my self, and not have been perhaps forgotten.'
- 58. Laura was notignorant of her own beauty, but no human being could less value the distinction. She was aware of the regularity of her features; but as she never used a looking-glass, unless for the obvious purpose of arranging her dress, she was insensible of the celestial charm which expression added to her face. The seriousness and dignity of her manners made it difficult to address her with common-place compliment; and she had accordingly never experienced any effect of her beauty, but one which was altogether disagreeable to her, that of attracting notice. To being the subject of observation, Laura retained that Caledonian dislike which once distinguished her country-women, before they were polished into that glitter which attracts the vulgar, and paid for the acquisition by the loss of the timidity which, like the ærugo of ancient coin, adds value in the eye of taste to intrinsic worth, while it shields even baser merit from contempt. Laura's courage failed her when, throwing open the door of a large room, Mrs de Courcy's servant announced Captain and Miss Montreville. But she revived when she perceived that the company consisted only of the mistress of the house, her son and daughter. Mrs de Courcy's appearance seemed to Laura very prepossessing. She still wore the dress of a widow; and her countenance bore the traces of what is called a green old age; for though the hair that shaded her commanding forehead was silver white, her dark eyes retained their brightness; and though her complexion was pale, it glowed at times with the roses of youth. The expression of her face, which was serious even to solemnity, brightened with a smile of inexpressible benevolence, as she received her guests; and, even in the difficulty with which she appeared to move, Laura found somewhat interesting. Her air and manners, without a tincture of fashion, spoke the gentlewoman. Her dress, her person, her demeanour, every thing about her seemed consistently respectable. The dinner was plain, but excellent. The few indispensable pieces of plate were antique and massive; and the only attendant who appeared, seemed to have grown gray in the service of the family. Laura had pleasure in observing, that the reverence with which this
- 59. old man addressedhis lady, softened into affectionate solicitude to please when he attended De Courcy, who, in his turn, seemed to treat him with the most considerate gentleness. Mrs De Courcy behaved to Laura with distinguished politeness; addressed her often; endeavoured to draw forth her latent powers; and soon made her sensible that the impression she had given, was no less favourable than that which she had received. Montague's conversation had its accustomed effect on Montreville, and the lively Harriet gave spirit to the whole. The evening passed most agreeably; and Laura was sorry when the hour of separation arrived. Mrs De Courcy courteously thanked her for her visit, and begged her to repeat it; but Harriet sportively objected: 'No, no,' said she, 'if you come back, you will not leave a heart among all the household— even old John's seems in danger.' 'Well, Mamma,' continued she, when Laura was gone, 'what do you think of my brother's beauty?' 'I think,' said Mrs De Courcy, 'that Montague's praises did her no more than justice. She is the most lovely, the most elegant woman I ever saw,' 'She is no doubt beautiful and interesting,' returned Harriet; 'but I must still think she has too much of the buckram of the old school to be elegant.' Montague bit his lip, and tried, before he spoke, to ascertain that he was not angry. 'You are too severe, Harriet,' said Mrs De Courcy. 'Miss Montreville's reserve is not stiffness—it is not buckram; it is rather the graceful drapery, embellishing what it veils.' 'Mother,' cried Montague, grasping her hand, 'you have more candour, sense, and taste, than all the misses in England.' 'Oh! pray, except Miss Montreville and the present company,' said Harriet, laughing. 'She, you know, is all perfection; and I have really candour, sense, and taste enough to admire her more than ever I did any woman, except my little self.' De Courcy threw his arm around her—'I see by that good-natured smile,' said he, 'that my dear Harriet has at least candour enough to pardon the folly of a wayward brother.' And, for the rest of the evening, he treated her with even more than his usual attentive kindness.
- 60. From this dayMiss De Courcy frequently accompanied her brother on his visits to the Montrevilles, and Laura was a welcome guest in Audley Street. By degrees Mrs De Courcy and she discovered the real worth of each other's character, and their mutual reserve entirely disappeared. Between Laura and De Courcy, almost from the first hour of their acquaintance, there seemed (to use the language of romance) a sympathy of souls;—an expression which, if it has any meaning, must mean the facility with which simple, upright, undesigning minds become intelligible to each other. Even the sarcastic Harriet found, in the chaste propriety of Laura's character, something to command respect; and in her gentleness and warmth of heart, something to engage affection; while, in her ideas, which solitude had slightly tinged with romance, though strong sense had preserved them from absurdity, and in her language, which sometimes rose to the very verge of poetry, she found constantly somewhat to interest and amuse. Meanwhile Montreville's dejection seemed to increase; and Laura's health and spirits, in spite of her efforts to support them, daily declined. Hargrave did not appear, and vainly did she endeavour to account for his absence. She at first conjectured that he had found it impossible to leave Scotland at the time he proposed; but a second letter from Mrs Douglas had mentioned his departure, and repeated the assurance that, however obtained, he had information of Laura's address, since he had undertaken to be the bearer of a letter from a neighbouring gentleman to Captain Montreville. She next supposed that he had stopped on the road, or quitted it on some errand of business or pleasure—but a newspaper account of a fête champêtre at Lady Bellamer's elegant villa at Richmond, was graced, among other fashionable names, with that of the handsome Colonel Hargrave, nephew and heir of Lord Lincourt. No supposition remained to be made, except the mortifying one, that three months of absence had erased her image from the fickle heart of Hargrave. She, who had herself consigned her lover to a banishment of two years, could not bear that he should voluntarily undergo one of a
- 61. few weeks. Nay,she had once herself resigned him; but to be herself resigned without effort, was more than she could endure. Her appetite, her sleep forsook her; her ordinary employments became irksome; and even the picture, the price of which was so soon to be necessary, she had not the spirits to finish. But one who was accustomed every night to examine the thoughts and actions of the day, was not likely to remain long a prey to inactive melancholy. Not satisfied with languid efforts in the discharge of duty, she reproached herself for every failure. She upbraided herself as a wicked and slothful servant, who, when the means of usefulness were put in her power, suffered them to remain unimproved; as a rebel who had deserted the service of her rightful master, to bow to the worse than Egyptian bondage of her passions. She accused herself of having given up her love, her wishes, her hopes and fears, almost her worship, to an idol; and no sooner did this thought occur to the pious mind of Laura, than she became resigned to her loss. She even felt grateful—with such gratitude as the wretch feels under the knife which amputates the morbid limb. Unused to let her self-reproaches pass without improvement, she resolved, by vigorous efforts, to become herself again. She even called in the aid of a decent pride. 'Shall I,' she cried, 'who have vowed to overcome the world—I who have called myself by that glorious name, a Christian, sink from these honours into a love-sick girl? Shall all my happiness, all my duties, the comfort of my father, the very means of his support, be sacrificed to a selfish passion? Or is a love, whose transient duration has proved its degenerate nature, of such value to me, that I must repay it with my whole heart and soul?' These reflections were not made at once, nor were they at once effectual; but, when made, they were called in as oft as the image of Hargrave intruded unbidden; and constant and regular occupation was again employed to second their operation. The picture was again resorted to; but, as it afforded rather an unsocial employment,
- 62. and as Laura'scompany was more than ever necessary to her father, it proceeded but slowly. De Courcy was now a daily visitor. Sometimes he brought books, and would spend hours in reading aloud, an accomplishment in which he excelled. Sometimes he would amuse the Captain and his daughter by experiments in his favourite science. With a gentleness peculiar to himself, he tried to prevent the little annoyances to which hypochondriacs are subject. He invented a hundred little indulgences for the invalid; and no day passed in which Montreville was not indebted for some comfort, or some amusement, to the considerate kindness of De Courcy. At times he would gently rally the Captain on his imaginary ailments, and sometimes prevailed on him to take the air in Mrs De Courcy's carriage: though to such a height had fancy worked upon him, that Montague found it impossible to persuade him that he was able to endure the fatigue of walking. To Laura, De Courcy's behaviour, uniformly respectful and attentive, was sometimes even tender. But, accustomed to see love only in the impassioned looks of Hargrave, to hear its accents only in his words of fire, she did not recognize it in a new form; and to consider De Courcy as a lover, never once entered her imagination. Captain Montreville was more clear-sighted, and hence arose much of the pleasure which he took in De Courcy's visits. Not that he was more knowing in the mysteries of love than his daughter; but he took it for granted, that no mortal could withstand her attractions; and he was persuaded that Laura would not withhold her heart, where she so freely expressed approbation. This opinion was a proof of the justice of the Captain's former confession, 'that women were creatures he did not understand.' Laura had never praised Hargrave. She never shrunk from De Courcy's eye,—she never felt embarrassed by his presence,—she treated him with the frankness of a sister; and though she reserved her commendations for his absence, she waited only for that to bestow them with all the warmth which his own merit and his attentions to her father could demand.
- 63. Meanwhile the Captaindid not, by a premature disclosure of his hopes, endanger their completion; and De Courcy continued unconsciously to foster in his bosom, a passion that was destined to destroy his peace.
- 64. CHAPTER XIII The pictureat last was finished, and Laura herself accompanied it to the print-shop. Wilkins immediately delivered to her the price, which, he said, had been for some time in his hands. It now occurred to Laura to ask who had been the purchaser of her work. 'Why, Ma'am,' said Wilkins, 'the gentleman desired me not to mention his name.' 'Indeed!' said Laura surprised. 'These were his orders. Ma'am, but I shouldn't think there could be any great harm in telling it just to you Ma'am.' 'I have no wish to hear it,' said Laura, with a look which compelled the confident to unwilling discretion; and again thanking him for the trouble he had taken, she returned home. The truth was, that De Courcy had foreseen the probability of Laura's question; and averse to be known to her under a character that savoured of patronage and protection, had forbidden the shopkeeper to mention who had purchased the pictures. Again did Laura, delighted, present to her father the produce of her labours, her warm heart glowing with the joys of usefulness. But not as formerly did he with pleasure receive the gift. With the fretfulness of disease, he refused to share in her satisfaction. Through the gloom of melancholy, every object appeared distorted; and Captain Montreville saw in his daughter's well-earned treasure only the wages of degrading toil. 'It is hard, very hard,' said he with a deep
- 65. sigh, 'that you,my lovely child, should be dependent on your daily labour for your support.' 'Oh call it not hard, my dear father,' cried Laura. 'Thanks, a thousand thanks to your kind foresight, which, in teaching me this blessed art, secured to me the only real independence, by making me independent of all but my own exertions.' 'Child,' said Montreville, fretfully, 'there is an enthusiasm about you that will draw you into ten thousand errors—you are quite mistaken in fancying yourself independent. Your boasted art depends upon the taste, the very caprice of the public for its reward; and you, of course, upon the very same caprice for your very existence.' 'It is true,' answered Laura mildly, 'that my success depends upon taste, and that the public taste is capricious; but some, I should hope, would never be wanting, who could value and reward the labours of industry—you observe,' added she with a smile, 'that I rest nothing upon genius.' 'Be that as it may,' returned Captain Montreville, with increasing querulousness, 'I cannot endure to see you degraded into an artist, and, therefore, I desire there may be no more of this traffic.' This was the first time that Montreville had ever resorted to the method well known and approved by those persons of both sexes, who, being more accustomed to the exercise of authority than of argument, choose to wield the weapon in the use of which practice has made them the most expert. Laura looked at him with affectionate concern—'Alas!' thought she, 'if bodily disease is pitiable, how far more deplorable are its ravages on the mind.' But even if her father had been in perfect health, she would not have chosen the moment of irritation for reply. Deeply mortified at this unexpected prohibition, she yet endeavoured to consider it as only one of the transient caprices of illness, and to find pleasure in the thought, that the hour was come, when De Courcy's daily visit would restore her father to some degree of cheerfulness. But De Courcy's visit made no one cheerful. He was himself melancholy and absent. He said he had only a few minutes to spare, yet lingered above an hour; often rose to go, yet irresolutely
- 66. resumed his seat.At last, starting up, he said, 'the longer I remain here, the more unwilling I am to go; and yet I must go, without even knowing when I may return.' 'Are you going to leave us?' said Montreville, in a tone of despondency, 'then we shall be solitary indeed.' 'I fear,' said Laura, looking with kind solicitude in De Courcy's face, 'that something distressing calls you away.' 'Distressing indeed,' said De Courcy. 'My excellent old friend Mr Wentworth has lost his only son, and I must bear the news to the parents.' 'Is there no one but you to do this painful office?' asked Montreville. 'None,' answered De Courcy, 'on whom it could with such propriety fall. Wentworth was one of my earliest friends, he was my father's early friend. I owe him a thousand obligations; and I would fain, if it be possible, soften this heavy blow. Besides,' added he, endeavouring to speak more cheerfully, 'I have a selfish purpose to serve,—I want to see how a Christian bears misfortune.' 'And can you fix no time for your return?' asked the Captain, mournfully. De Courcy shook his head. 'You will not return while your presence is necessary to Mr Wentworth,' said Laura, less anxious to regain De Courcy's society, than that he support the character of benevolence with which her imagination had justly vested him. Grieved by the prospect of losing his companion, fretted by an indefinite idea that he was wrong in his ungracious rejection of his daughter's efforts to serve him, ashamed of his distempered selfishness, yet unable to conquer it, Captain Montreville naturally became more peevish; for the consciousness of having acted wrong, without the resolution to repair the fault, is what no temper can stand. 'Your charity is mighty excursive Laura,' said he. 'If Mr De Courcy delays his return long, I shall probably not live to profit by it.' Laura, whose sweetness no captious expressions could ruffle, would have spoken to turn her father's view to brighter prospects; but the rising sob choked her voice, and courtesying hastily to De Courcy, she left the room. De Courcy now no longer found it difficult to depart. He soon bade the Captain farewell, promising to return as soon as it was possible, though he had no great faith in Montreville's dismal prediction, uttered in the true spirit of hypochondriasis, that he would come but to lay his head in his grave.
- 67. As he wasdescending the stairs, Laura, who never forgot in selfish feeling to provide for the comfort of others, followed him, to beg that when he had leisure, he would write to her father. Laura blushed and hesitated as she made this request, not because she had in making it any selfish motive whatever, but purely because she was unused to ask favours. Flattered by the request, but much more by her confusion, De Courcy glowed with pleasure. 'Certainly I shall write,' said he with great animation, 'if you—I mean if Captain Montreville wish it.' These words, and the tone in which they were uttered, made Laura direct a look of inquiry to the speaker's face, where his thoughts were distinctly legible; and she no sooner read then, than, stately and displeased, she drew back. 'I believe it will give my father pleasure to hear from you, sir,' said she, and coldly turned away. 'Is there no man,' thought she, 'exempt from this despicable vanity—from the insignificant Warren to the respectable De Courcy?' Poor Montague would fain have besought her forgiveness for his presumption in supposing it possible that she could have any pleasure in hearing of him; but the look with which she turned from him, left him no courage to speak to her again, and he mournfully pursued his way to Audley Street. He was scarcely gone when Warren called, and Laura, very little displeased for his company, took shelter in her own room. Her father, however, suffered no inconvenience from being left alone to the task of entertaining his visitor, for Warren found means to make the conversation sufficiently interesting. He began by lamenting the Captain's long detention from his home, and condoled with him upon the effects which London air had produced upon his health. He regretted that Mr Williams's absence from town had retarded the final settlement of Montreville's business; informed him that Mr Baynard's executors had appointed an agent to inspect his papers; and finally, surprised him by an unconditional offer to sign a new bond for the annuity. He could not bear, he said, to think of the Captain's being detained in London to the prejudice of his health, especially as it was evident that Miss
- 68. Montreville's suffered fromthe same cause. He begged that a regular bond might be drawn up, which he would sign at a moment's notice, and which he would trust to the Captain's honour to destroy, if it should be found that the £1500, mentioned as the price of the annuity, had never been paid. At this generous proposal, surprise and joy almost deprived Montreville of the power of utterance; gratefully clasping Warren's hand, 'Oh, sir,' he exclaimed, 'you have, I hope, secured an independence for my child. I thank you—with what fervour, you can never know till you are yourself a father.' Seemingly anxious to escape from his thanks, Warren again promised that he would be ready to sign the bond on the following day, or as soon as it was ready for signature. Captain Montreville again began to make acknowledgements, but Warren, who appeared rather distressed than gratified by them, took his leave, and left the Captain to the joyful task of communicating the news to Laura. She listened with grateful pleasure. 'How much have I been to blame,' said she, 'for allowing myself to believe that a little vanity necessarily excluded every kind and generous feeling. What a pity it is that this man should condescend to such an effeminate attention to trifles!' Lost to the expectation, almost to the desire of seeing Hargrave, she had now no tie to London, but one which was soon to be broken, for Mrs and Miss De Courcy were about to return to Norwood. With almost unmixed satisfaction, therefore, she heard her father declare, that in less than a week he should be on his way to Scotland. With pleasure she looked forward to revisiting her dear Glenalbert, and anticipated the effects of its quiet shades and healthful air upon her father. Already she beheld her home, peaceful and inviting, as when, from the hill that sheltered it, she last looked back upon its simple beauties. She heard the ripple of its waters; she trod the well-known path; met the kind familiar face, and listened to the cordial welcome, with such joy as they feel who return from the land of strangers.
- 69. Nor was Montrevilleless pleased with the prospect of returning to his accustomed comforts and employments—of feeling himself once more among objects which he could call his own. His own! There was magic in the word, that transformed the cottage at Glenalbert into a fairy palace—the garden and the farm into a little world. To leave London interfered indeed with his hopes of De Courcy as a lover for his daughter; but he doubted not that the impression was already made, and that Montague would follow Laura to Scotland. His mind suddenly relieved from anxiety, his spirits rose, all his constitutional good nature returned, and he caressed his daughter with a fondness that seemed intended to atone for the captious behaviour of the morning. At dinner he called for wine, a luxury in which he rarely indulged, drank to their safe arrival at Glenalbert, and obliged Laura to pledge him to the health of Warren. To witness her father's cheerfulness was a pleasure which Laura had of late tasted so sparingly, that it had the most exhilarating effect upon her spirits; and neither De Courcy nor Hargrave would have been much gratified, could they have seen the gaiety with which she supported the absence of the one, and the neglect of the other. She was beginning to enjoy one of those cheerful domestic evenings which had always been her delight, when Miss Dawkins came to propose that she should accompany her and her mother on a visit to Mrs Jones. Laura would have excused herself, by saying, that she could not leave her father alone; but the Captain insisted upon her going, and declared that he would himself be of the party. She had therefore no apology, and, deprived of the amusement which she would have preferred, contentedly betook herself to that which was within her reach. She did not sit in silent contemplation of her own superiority, or of the vulgarity of her companions; nor did she introduce topics of conversation calculated to illustrate either; but having observed that even the most ignorant have some subject on which they can talk with ease and pleasure, and even be heard with advantage, she suffered others to lead the discourse, rightly conjecturing that they would guide it to the channel which they
- 70. judged most favourableto their own powers. She was soon engaged with Mrs Dawkins in a dissertation on various branches of household economy, and to the eternal degradation of her character as a heroine, actually listened with interest to the means of improving the cleanliness, beauty, and comfort of her dwelling. Mrs Jones was highly flattered by the Captain's visit, and exerted herself to entertain him, her husband being inclined to taciturnity by a reason which Bishop Butler has pronounced to be a good one. Perceiving that Montreville was an Englishman, she concluded that nothing but dire necessity could have exiled him to Scotland. She inquired what town he lived in; and being answered that his residence was many miles distant from any town, she held up her hands in pity and amazement. But when she heard that Montreville had been obliged to learn the language of the Highlands, and that it was Laura's vernacular tongue, she burst into an exclamation of wonder. 'Mercy upon me,' cried she, 'can you make that outlandish spluttering so as them savages can know what you says? Well, if I had been among them a thousand years, I should never have made out a word of their gibberish.' 'The sound of it is very uncouth to a stranger,' said Captain Montreville, 'but now I have learnt to like it.' 'And do them there wild men make you wear them little red and green petticoats?' asked Mrs Jones, in a tone of compassionate inquiry. 'Oh no,' said Captain Montreville, 'they never interfered with my dress. But you seem quite acquainted with the Highlands. May I ask if you have been there?' 'Aye, that I have, to my sorrow,' said Mrs Jones; and forthwith proceeded to recount her adventures, pretty nearly in the same terms as she had formerly done to Laura. 'And what was the name of this unfortunate place,' inquired the captain, when, having narrated the deficiency of hot rolls, Mrs Jones made the pause in which her auditors were accustomed to express their astonishment and horror. 'That was what I asked the waiter often and often,' replied she, 'but I could never make head or tail of what he said. Sometimes it sounded like A rookery; sometimes like one thing,
- 71. sometimes like another.So I takes the roadbook, and looks it out, and it looked something like A rasher, only not right spelt. So, thinks I, they'll call it A rasher, because there is good bacon here; and I asked the man if they were famous for pigs; and he said, no, they got all their pigs from the manufactory in Glasgow, and that they weren't famous for any thing but fresh herrings, as are catched in that black Loch-Lomond, where they wanted me to go.' 'Kate,' said Mr Jones, setting down his tea-cup, and settling his hands upon his knees, 'you know I think you're wrong about them herrings.' 'Mr Jones,' returned the lady, with a look that shewed that the herrings had been the subject of former altercation, 'for certain the waiter told me that they came out of the loch, and to what purpose should he tell lies about it.' 'I tells you, Kate, that herrings come out of the sea,' said Mr Jones. 'Well, that loch is a great fresh water sea,' said Mrs Jones. 'Out of the salt sea,' insisted Mr Jones. 'Aye,' said Mrs Jones, 'them salt herrings as we gets here, but it stands to reason, Mr Jones, that the fresh herrings should come out of fresh water.' 'I say, cod is fresh, and does'n't it come out of the sea? answer me that, Mrs Jones.' 'It is no wonder the cod is fresh,' returned the lady, 'when the fishmongers keep fresh water running on it day and night.' 'Kate, it's of no use argufying, I say herrings come out of the sea. What say you, Sir?' turning to Captain Montreville. The Captain softened his verdict in the gentleman's favour, by saying, that Mrs Jones was right in her account of the waiter's report, though the man, in speaking of 'the loch,' meant not Loch-Lomond, but an arm of the sea. 'I know'd it,' said Mr Jones triumphantly, 'for haven't I read it in the newspaper as Government offers a reward to any body that'll put most salt upon them Scotch herrings, and is'n't that what makes the salt so dear?' So having settled this knotty point to his own satisfaction, Mr Jones again applied himself to his tea. 'Did you return to Glasgow by the way of Loch-Lomond?' inquired Captain Montreville. 'Ay,' cried Mrs Jones, 'that was what the people of the inn wanted us to do; but then I looked out, and seed a matter
- 72. of forty ofthem there savages, with the little petticoats and red and white stockings, loitering and lolling about the inn-door, doing nothing in the varsal world, except wait till it was dark to rob and murder us all, bless us! So, thinks I, let me once get out from among you in a whole skin, and catch me in the Highlands again; so as soon as the chaise could be got, we just went the way we came.' 'Did you find good accommodation in Glasgow,' said the Captain. 'Yes,' replied Mrs Jones; 'but after all, Captain, there's no country like our own;—do you know, I never got so much as a buttered muffin all the while I was in Scotland?' The conversation was here interrupted by an exclamation from Mrs Dawkins, who, knowing that she had nothing new to expect in her daughter's memoirs of her Scotish excursion, had continued to talk with Laura apart. 'Goodness me!' she cried, 'why Kate, as sure as eggs, here's Miss never seed a play in all her life!' 'Never saw a play! Never saw a play!' exclaimed the landlord and landlady at once. 'Well, that's so odd; but to be sure, poor soul, how should she, among them there hills.' 'Suppose,' said Mrs Jones, 'we should make a party, and go tonight.—We shall be just in time.' Laura was desirous to go: her father made no objection; and Mr Jones, with that feeling of good-natured self-complacency which most people have experienced, arising from the discovery that another is new to a pleasure with which he himself is familiar, offered, as he expressed it, 'to do the genteel thing, and treat her himself.' The party was speedily arranged, and Laura soon found herself seated in the pit of the theatre. The scene was quite new to her; for her ignorance of public places was even greater than her companions had discovered it to be. She was dazzled with the glare of the lights, and the brilliancy of the company, and confused with the murmur of innumerable voices; but the curtain rose, and her attention was soon confined to the stage. The play was the Gamester, the most domestic of our tragedies; and, in the inimitable representation of Mrs Beverly, Laura found an illusion strong enough to absorb for the time every faculty of her soul. Of the actress she
- 73. thought not; butshe loved and pitied Mrs Beverly with a fervour that made her insensible to the amusement which she afforded to her companions. Meanwhile her countenance, as beautiful, almost as expressive, followed every change in that of Mrs Siddons. She wept with her; listened, started, rejoiced with her; and when Mrs Beverly repulsed the villain Stukely, Laura's eyes too flashed with 'heaven's own lightnings.' By the time the representation was ended, she was so much exhausted by the strength and rapidity of her emotions, that she was scarcely able to answer to the questions of 'How have you been amused?' and 'How did you like it?' with which her companions all at once assailed her. 'Well,' said Miss Julia, when they were arrived at home, 'I think nothing is so delightful as a play. I should like to go every night—shouldn't you?' 'No,' answered Laura. 'Once or twice in a year would be quite sufficient for me. It occupies my thoughts too much for a mere amusement.' In the course of the two following days, Laura had sketched more than twenty heads of Mrs Siddons, besides completing the preparations for her journey to Scotland. On the third, the Captain, who could now smile at his own imaginary debility, prepared to carry the bond to receive Mr Warren's signature. The fourth was to be spent with Mrs De Courcy; and on the morning of the fifth, the travellers intended to depart. On the appointed morning, Captain Montreville set out on an early visit to Portland Street, gaily telling his daughter at parting that he would return in an hour or two, with her dowery in his pocket. When he knocked at Mr Warren's door, the servant informed him that his master had gone out, but that expecting the Captain to call, he had left a message to beg that Montreville would wait till he returned, which would be very soon. The Captain was then shewn into a back parlour, where he endeavoured to amuse himself with some books that were scattered round the room. They consisted of amatory poems and loose novels, and one by one he threw them aside in disgust, lamenting that one who was capable of a kind and generous action should seek pleasure
- 74. in such debasingstudies. The room was hung with prints and pictures, but they partook of the same licentious character; and Montreville shuddered, as the momentary thought darted across his mind, that it was strange that the charms of Laura had made no impression on one whose libertinism in regard to her sex was so apparent. It was but momentary. 'No!' thought he, 'her purity would awe the most licentious; and I am uncandid, ungrateful, to harbour even for a moment such an idea of the man who has acted towards her and me with the most disinterested benevolence.' He waited long, but Warren did not appear; and he began to blame himself for having neglected to fix the exact time of his visit. To remedy this omission, he rang for writing materials, and telling the servant that he could stay no longer, left a note to inform Mr Warren that he would wait upon him at twelve o'clock next day. The servant, who was Mr Warren's own valet, seemed unwilling to allow the Captain to depart, and assured him that he expected his master every minute; but Montreville, who knew that there was no depending upon the motions of a mere man of pleasure, would be detained no longer. He returned home, and finding the parlour empty, was leaving it to seek Laura in her painting-room, when he observed a letter lying on the table addressed to himself. The hand-writing was new to him. He opened it—the signature was equally so. The contents were as follows:— 'Sir, The writer of this letter is even by name a stranger to you. If this circumstance should induce you to discredit my information, I offer no proof of my veracity but this simple one, that obviously no selfish end can be served by my present interference. Of the force of my motive you cannot judge, unless you have yourself lured to destruction the heart that trusted you,—seen it refuse all comfort,— reject all reparation,—and sink at last in untimely decay. From a fate
- 75. like this, thoughnot softened like this by anxious tenderness, nor mourned like this by remorseless pity, but aggravated by being endured for one incapable of any tender or generous feeling, it is my purpose, Sir, to save your daughter. I was last night one of a party where her name was mentioned;—where she was described as lovely, innocent, and respectable; yet the person who so described her, scrupled not to boast of a plan for her destruction. In the hope (why should I pretend a better motive) of softening the pangs of late but bitter self-reproach, by saving one fellow-creature from perhaps reluctant ruin, one family from domestic shame, I drew from him your address, and learnt that to ingratiate himself with you, and with his intended victim, he has pretended to offer as a gift, what he knew that he could not long withhold. He means to take the earliest opportunity of inveigling her from your care, secure, as he boasts, of her pardon in her attachment. Ill, indeed, does her character, even as described by him, accord with such a boast; yet even indifference might prove no guard against fraud, which, thus warned, you may defy. A fear that my intention should be frustrated by the merited contempt attached to anonymous information, inclines me to add my name, though aware that it can claim no authority with a stranger. 'I am, Sir, 'Your obedient Servant, 'Philip Wilmot.' Captain Montreville read this letter more than once. It bore marks of such sincerity that he knew not how to doubt of the intelligence it gave; and he perceived with dismay, that the business which he had considered as closed, was as far as ever from a conclusion; for how could he accept a favour which he had been warned to consider as the wages of dishonour. For Laura he had indeed no fear. She was no less safe in her own virtue and discretion, than in the contemptuous pity with which she regarded Warren. This letter would put her upon her guard against leaving the house with him,
- 76. which Captain Montrevillenow recollected that he had often solicited her to do, upon pretence of taking the air in his curricle. But must he still linger in London; still be cheated with vain hopes; still fear for the future subsistence of his child; still approach the very verge of poverty; perhaps be obliged to defend his rights by a tedious law-suit? His heart sank at the prospect, and he threw himself on a seat, disconsolate and cheerless. He had long been in the habit of seeking relief from every painful feeling in the tenderness of Laura,—of finding in her enduring spirit a support to the weakness of his own; and he now sought her in the conviction that she would either discover some advantage to be drawn from this disappointment, or lighten it to him by her affectionate sympathy. He knocked at the door.—She did not answer. He called her.—All was silent. He rang the bell, and inquired whether she was below, and was answered that she had gone out with Mr Warren in his curricle two hours before. The unfortunate father heard no more. Wildly striking his hand upon his breast, 'She is lost!' he cried, and sunk to the ground. The blood burst violently from his mouth and nostrils, and he became insensible. The family were soon assembled round him; and a surgeon being procured, he declared that Montreville had burst a blood vessel, and that nothing but the utmost care and quiet could save his life. Mrs Dawkins, with great humanity, attended him herself, venting in whispers to the surgeon her compassion for Montreville, and her indignation against the unnatural desertion of Laura, whom she abused as a methodistical hypocrite, against whom her wrath was the stronger because she could never have suspected her. Montreville no sooner returned to recollection, than he declared his resolution instantly to set off in search of his child. In vain did the surgeon expostulate, and assure him that his life would be the forfeit: his only answer was, 'Why should I live? She is lost.' In pursuance of his design, he tried to rise from the bed on which he
- 77. had been laid;but exhausted nature refused to second him, and again he sunk back insensible. When Montreville called in Portland Street, the servant had deceived him in saying that Warren was not at home. He was not only in the house, but expected the Captain's visit, and prepared to take advantage of it, for the accomplishment of the honourable scheme of which he had boasted to his associates. As soon, therefore, as the servant had disposed of Montreville, Warren mounted his curricle, which was in waiting at a little distance, and driving to Mrs Dawkins's, informed Laura that he had been sent to her by her father, who proposed carrying her to see the British Museum, and for that purpose was waiting her arrival in Portland Street. Entirely unsuspicious of any design, Laura accompanied him without hesitation; and though Portland Street appeared to her greatly more distant than she had imagined it, it was not till having taken innumerable turns, she found herself in an open road, that she began to suspect her conductor of having deceived her. 'Whither have you taken me, Mr Warren?' she inquired: 'This road does not lead to Portland Street.' 'Oh yes, it does,' answered Warren, 'only the road is a little circuitous.' 'Let us immediately return to the straight one then,' said Laura. 'My father will be alarmed, and conclude that some accident has happened to us.' 'Surely, my charming Miss Montreville,' said Warren, still continuing to drive on, 'you do not fear to trust yourself with me.' 'Fear you!' repeated Laura, with involuntary disdain. 'No, but I am at a loss to guess what has encouraged you to make me the companion of so silly a frolic. I suppose you mean this for an ingenious joke upon my father.' 'No, 'pon my soul,' said the beau, a little alarmed by the sternness of her manner, 'I meant nothing but to have an opportunity of telling you that I am quite in love with you,—dying for you,—faith I am.' 'You should first have ascertained,' answered Laura, 'whether I was likely to think the secret worth a hearing. I desire you will instantly return.'
- 78. The perfect composureof Laura's look and manner (for feeling no alarm she shewed none) made Warren conclude that she was not averse to being detained; and he thought it only necessary that he should continue to make love, to induce her quietly to submit to go on for another half mile, which would bring them to a place where he thought she would be secure. He began, therefore, to act the lover with all the energy he could muster; but Laura interrupted him. 'It is a pity,' said she, with a smile of calm contempt, 'to put a stop to such well-timed gallantry, which is indeed just such as I should have expected from Mr Warren's sense and delicacy. But I would not for the sake of Mr Warren's raptures, nor all else that he has to offer, give my father the most momentary pain, and therefore if you do not suffer me to alight this instant, I shall be obliged to claim the assistance of passengers on an occasion very little worthy of their notice.' Her contumelious manner entirely undeceived her companion in regard to her sentiments; but it had no other effect upon him, except that of adding revenge to the number of his incitements; and perceiving that they were now at a short distance from the house whither he intended to convey her, he continued to pursue his way. Laura now rose from her seat, and seizing the reins with a force that made the horses rear, she coolly chose that moment to spring from the curricle; and walked back towards the town, leaving her inammorato in the utmost astonishment at her self-possession, as well as rage at her disdainful treatment. She proceeded till she came to a decent-looking shop, where she entered; and, begging permission to sit down, dispatched one of the shop-boys in search of a hackney-coach. A carriage was soon procured, and Laura, concluding that her father, tired of waiting for her, must have left Portland Street, desired to be driven directly home. As she entered the house, she was met by Mrs Dawkins. 'So Miss,' cried she, 'you have made a fine spot of work on't. You have murdered your father.' 'Good heavens!' cried Laura, turning as pale
- 79. as death, 'whatis it you mean? where is my father?' 'Your father is on his deathbed Miss, and you may thank your morning rides for it. Thinking you were off, he burst a blood-vessel in the fright, and the doctor says, the least stir in the world will finish him.' Laura turned sick to death. Cold drops stood upon her forehead; and she shook in every limb. She made an instinctive attempt to ascend the stair; but her strength failed her, and she sunk upon the steps. The sight of her agony changed in a moment Mrs Dawkins's indignation to pity. 'Don't take on so, Miss,' said she, 'to be sure you didn't mean it. If he is kept quiet, he may mend still, and now that you're come back too.—By the bye, I may as well run up and tell him.' 'Oh stop!' cried Laura, reviving at once in the sudden dread that such incautious news would destroy her father, 'Stay,' said she, pressing with one hand her bursting forehead, while with the other she detained Mrs Dawkins.—'Let me think, that we may not agitate him. Oh no! I cannot think;' and leaning her head on Mrs Dawkins' shoulder, she burst into an agony of tears. These salutary tears restored her recollection, and she inquired whether the surgeon, of whom Mrs Dawkins had spoken, was still in the house. Being answered, that he was in Montreville's apartment, she sent to beg that he would speak with her. He came, and she entreated him to inform her father, with the caution which his situation required, that she was returned and safe. She followed him to the door of Montreville's apartment, and stood listening in trembling expectation to every thing that stirred within. At last she received the wished-for summons. She entered; she sprang towards the bed. 'My child!' cried Montreville, and he clasped her to his bosom, and sobbed aloud. When he was able to speak, 'Oh Laura,' said he, 'tell me again that you are safe, and say by what miracle, by what unheard-of mercy, you have escaped.' 'Compose yourself, my dearest father, for Heaven's sake,' cried Laura. 'I am indeed safe, and never have been in danger. When Warren found that I refused to join in his frolic, he did not attempt to prevent me from returning home.' She then briefly related the affair as it had appeared to her,
- 80. suppressing Warren's rhapsodies,from the fear of irritating her father; and he, perceiving that she considered the whole as a frolic, frivolous in its intention, though dreadful in its effects, suffered her to remain in that persuasion. She passed the night by his bed-side, devoting every moment of his disturbed repose to fervent prayers for his recovery.
- 81. CHAPTER XIV From feverishand interrupted sleep, Montreville awoke unrefreshed; and the surgeon, when he repeated his visit, again alarmed Laura with representations of her father's danger, and assurances that nothing but the most vigilant attention to his quiet could preserve his life. The anguish with which Laura listened to this sentence she suppressed, lest it should injure her father. She never approached him but to bring comfort; she spoke to him cheerfully, while the tears forced themselves to her eyes; and smiled upon him while her heart was breaking. She felt what he must suffer, should the thought occur to him that he was about to leave her to the world, unfriended and alone; and she never mentioned his illness to him unless with the voice of hope. But of the danger which she strove to disguise, Montreville was fully sensible; and though he forbore to shock her by avowing it explicitly, he could not, like her, suppress his fears. He would sometimes fervently wish that he could see his child safe in the protection of Mrs Douglas; and sometimes, when Laura was bending over him in the tenderest sympathy, he would clasp her neck, and cry, with an agony that shook his whole frame, 'What—Oh what will become of thee!' He seemed anxious to know how long Mrs De Courcy was to remain in town, and inquired every hour whether Montague was not
- 82. returned. Full welldid Laura guess the mournful meaning of these questions. Full well did they remind her, that when the De Courcy family left London, she with her dying father would amidst this populous wilderness be alone. She anticipated the last scene of this sad tragedy; when, amidst busy thousands, a senseless corpse would be her sole companion. She looked forward to its close, when even this sad society would be withdrawn. Human fortitude could not support the prospect; and she would rush from her father's presence, to give vent to agonies of sorrow. But the piety of Laura could half-invest misfortune with the character of blessing; as the mists that rise to darken the evening sun are themselves tinged with his glory. She called to mind the gracious assurance which marks the afflicted who suffer not by their own guilt or folly as the favoured of Heaven; and the more her earthly connections seemed dissolving, the more did she strive to acquaint herself with Him, from whose care no accident can sever. To this care she fervently committed her father; praying that no selfish indulgence of her grief might embitter his departure; and resolving by her fortitude to convince him that she was able to struggle with the storm from which he was no longer to shelter her. The day succeeding that on which Montreville was taken ill had been set apart for a farewell visit to Mrs De Courcy; and Laura's note of mournful apology, was answered by a kind visit from Harriet. Unconscious of the chief cause of her father's impatience for Montague's return, Laura wishing to be the bearer of intelligence which she knew would cheer him, inquired anxiously when Miss De Courcy expected her brother. But De Courcy's motions depended upon the spirits of his venerable friend, and Harriet knew not when he might be able to leave Mr Wentworth. It was even uncertain whether for the present he would return to town at all, as in another week Mrs De Courcy meant to set out for Norwood. Laura softened this unpleasing news to her father; she did not name the particular time of Mrs De Courcy's departure, and she suffered him still confidently to expect the return of his favourite.
- 83. The next daybrought a letter from De Courcy himself, full of affectionate solicitude for the Captain's health and spirits; but evidently written in ignorance of the fatal change that had taken place since his departure. In this letter the name of Laura was not mentioned, not even in a common compliment, and Montreville remarked to her this omission. 'He has forgotten it,' answered Laura, —'his warm heart is full of his friend's distress and yours, and has not room for more ceremony.' 'I hope,' said Montreville, emphatically, 'that is not the reason.' 'What is then the reason?' inquired Laura; but Montreville did not speak, and she thought no more of De Courcy's little omission. Her father, indeed, for the present, occupied almost all her earthly thoughts, and even her prayers rose more frequently for him than for herself. Except during the visits of Montreville's surgeon, she was Montreville's sole attendant; and, regardless of fatigue, she passed every night by his bed-side, every day in ministering to his comfort. If, worn out with watching, she dropt asleep, she started again at his slightest motion, and obstinately refused to seek in her own chamber a less interrupted repose. 'No,' thought she, 'let my strength serve me while I have duties to perform, while my father lives to need my efforts; then may I be permitted to sink to early rest, and the weary labourer, while yet it is but mornings be called to receive his hire.' The desertion of Hargrave, whom she had loved with all the ardour of a warm heart and a fervid imagination, the death of her father so fast approaching, her separation from every living being with whom she could claim friendship or kindred, seemed signals for her to withdraw her affections from a world where she would soon have nothing left to love or to cherish. 'And be it so,' thought she,—'let me no longer grovel here in search of objects which earth has not to offer—objects fitted for unbounded and unchangeable regard. Nor let me peevishly reject what this world really has to give, the opportunity to prepare for a better. This it bestows even on me; and
- 84. a few childishbaubles are all else that it reserves for those who worship it with all their soul, and strength, and mind.' No mortal can exist without forming some wish or hope. Laura hoped that she should live while she could be useful to her father; and she wished that she might not survive him. One only other wish she had, and that was for De Courcy's return; for Montreville, whose spirits more than shared his bodily languor, now seldom spoke, but to express his longing for the presence of his favourite. Laura continued to cheer him with a hope which she herself no longer felt; for now three days only remained ere Mrs De Courcy was to quit London. The departure of their friends Laura resolved to conceal from her father, that, believing them to be near, he might feel himself the less forlorn; and this she thought might be practicable, as he had never since his illness expressed any wish to quit his bed, or to see Miss De Courcy when she came. In Montreville's darkened apartment, without occupation but in her cares for him, almost without rest, had Laura passed a week, when she was one morning summoned from her melancholy charge, to attend a visitor. She entered the parlour. 'Mr De Courcy!' she exclaimed, springing joyfully to meet him, 'thank Heaven you are come!' But not with equal warmth did De Courcy accost her. The repulsive look she had given him at parting was still fresh in his recollection; and, with a respectful distant bow, he expressed his sorrow for Captain Montreville's illness. 'Oh he is ill, indeed!' said Laura, the faint hectic of pleasure fading suddenly from her cheek. 'Earnestly has he longed for your return; and we feared,' said she, with a violent effort suppressing her tears, 'we feared that you might not have come till—till all was over.' 'Surely Miss Montreville,' said De Courcy, extremely shocked, 'surely you are causelessly alarmed.' 'Oh no,' cried Laura, 'he cannot live!' and no longer able to contain her emotion, she burst into a passion of tears. Forced entirely from his guard by her grief, Montague threw himself on the seat beside her. 'Dearest of human beings,' he exclaimed, 'Oh that I could shield thee from every sorrow!' But absorbed in her distress, Laura heeded him
- 85. not; and thenext moment, sensible of his imprudence, he started from her side, and retreated to a distant part of the room. As soon as she was again able to command herself, she went to inform her father of De Courcy's arrival. Though told with the gentlest caution, Montreville heard the news with extreme emotion. He grasped Laura's hand; and, with tears of joy streaming down his pale cheeks, said,—'Heaven be praised! I shall not leave thee quite desolate.' Laura herself felt less desolate and she rejoiced even for herself, when she once more saw De Courcy seated beside her father. It was only the morning before, that a letter from Harriet had informed her brother of Montreville's illness and of Laura's distress. To hear of that distress, and to remain at a distance was impossible; and Montague had left Mr Wentworth's within the hour. He had travelled all night; and, without even seeing his mother and sister, had come directly to Captain Montreville's lodgings. He was shocked at the death-like looks of Montreville, and still more at those of Laura. Her eyes were sunk, her lips colourless, and her whole appearance indicated that she was worn out with fatigue and wretchedness. Yet De Courcy felt, that never in the bloom of health and beauty, had she been so dear to him, and scarcely could he forbear from addressing her in the accents of compassion and love. Montreville wishing to speak with him alone, begged of Laura to leave him for a while to De Courcy's care, and endeavour to take some rest. She objected that Montague had himself need of rest, having travelled all night; but when he assured her, that even if she drove him away he would not attempt to sleep, she consented to retire, and seek the repose of which she was so much in want. When they were alone, Montreville shewed De Courcy the warning letter; and related to him the baseness of Warren and Laura's escape. Montague listened to him with intense interest. He often changed colour, and his lips quivered with emotion; and, when her father described the manner in which she had accomplished her escape, he exclaimed with enthusiasm, 'Yes, she is superior to every
- 86. weakness, as sheis alive to every gentle feeling.' Montreville then dwelt upon her unremitting care of him—on the fortitude with which she suppressed her sorrow, even while its violence was perceptibly injuring her health. 'And is it to be wondered at,' said he, 'that I look forward with horror to leaving this lovely excellent creature in such a world, alone and friendless?' 'She shall never be friendless,' cried De Courcy. 'My mother, my sister, shall be her friends, and I will'—He stopped abruptly, and a heavy sigh burst from him. Recovering himself, he resumed, 'You must not talk so despondingly. You will live long, I trust, to enjoy the blessing of such a child.' Montreville shook his head, and remained silent. He was persuaded that De Courcy loved his daughter, and would fain have heard an explicit avowal that he did. To have secured to her the protection of Montague would have destroyed the bitterness of death. Had Laura been the heiress of millions, he would have rejoiced to bestow her and them upon De Courcy. But he scorned to force him to a declaration, and respected her too much to make an approach towards offering her to any man's acceptance. He was at a loss to imagine what reason withheld De Courcy from avowing an attachment which he was convinced that he felt. When he considered his favourite's grave reflecting character, he was rather inclined to believe that he was cautiously ascertaining the temper and habits of the woman with whom he meant to spend his life. But the warmth of approbation with which he mentioned Laura, seemed to indicate that his opinion of her was already fixed. It was possible, too, that De Courcy wished to secure an interest in her regard before he ventured formally to petition for it. Whatever was the cause of Montague's silence, the Captain anticipated the happiest consequences from his renewed intercourse with Laura; and he resolved that he would not, by any indelicate interference, compel him to precipitate his declaration. He therefore changed the conversation, by inquiring when Mrs De Courcy was to leave town. Montague answered, that as he had not seen his mother since his return, he did not exactly know what time was fixed for her
- 87. departure: 'but,' saidhe, 'whenever she goes, I shall only attend her to Norwood, and return on the instant; nor will I quit you again, till you are much, much better, or till you will no longer suffer me to stay.' Montreville received this promise with gratitude and joy; and De Courcy persuaded himself, that in making it, he was actuated chiefly by motives of friendship and humanity. He remained with Montreville till the day was far advanced, and then went to take a late dinner in Audley Street. Next morning, and for several succeeding days, he returned, and spent the greatest part of his time in attending, comforting, and amusing the invalid. He prevailed on his mother to delay her departure, that he might not be obliged immediately to leave his charge. He soothed the little impatiences of disease; contrived means to mitigate the oppressiveness of debility; knew how to exhilarate the hour of ease; and watched the moment, well known to the sickly, when amusement becomes fatigue. Laura repaid these attentions to her father with gratitude unutterable. Often did she wish to thank De Courcy as he deserved; but she felt that her acknowledgements must fall far short of her feelings and of his deserts, if they were not made with a warmth, which to a man, and to a young man, she revolted from expressing. She imagined, too, that to one who sought for friendship, mere gratitude might be mortifying; and that it might wound the generous nature of Montague to be thanked as a benefactor, where he wished to be loved as an equal. She therefore did not speak of, or but slightly mentioned, her own and her father's obligations to him; but she strove to repay them in the way that would have been most acceptable to herself, by every mark of confidence and good will. Here no timidity restrained her; for no feeling that could excite timidity at all mingled with her regard for De Courcy. But, confined to her own breast, her gratitude became the stronger; and if she had now had a heart to give, to Montague it would have been freely given.
- 88. Meanwhile the spiritsof Montreville lightened of a heavy load, by the assurance that, even in case of his death, his daughter would have a friend to comfort and protect her, his health began to improve. He was able to rise; and one day, with the assistance of Montague's arm, surprised Laura with a visit in the parlour. The heart of Laura swelled with transport when she saw him once more occupy his accustomed seat in the family-room, and received him as one returned from the grave. She sat by him, holding his hand between her own, but did not try to speak. 'If it would not make you jealous, Laura,' said Montreville, 'I should tell you that Mr De Courcy is a better nurse than you are. I have recruited wonderfully since he undertook the care of me. More indeed than I thought I should ever have done.' Laura answered only by glancing upon De Courcy a look of heartfelt benevolence and pleasure. 'And yet,' said Montague, 'it is alleged that no attentions from our own sex are so effectual as those which we receive from the other. How cheaply would bodily suffering purchase the sympathy, the endearments of'—the name of Laura rose to his lips, but he suppressed it, and changed the expression to 'an amiable woman.' 'Is it indeed so?' cried Laura, raising her eyes full of grateful tears to his face. 'Oh then, if sickness or sorrow must be your portion, may your kindness here be repaid by some spirit of peace in woman's form—some gentleness yet more feminine than De Courcy's!' The enthusiasm and gratitude had hurried Laura into a warmth which the next moment covered her with confusion; and she withdrew her eyes from De Courcy's face before she had time to remark the effect of these, the first words of emotion that ever she had addressed to him. The transport excited by the ardour of her expressions, and the cordial approbation which they implied, instantly gave way to extreme mortification. 'She wishes,' thought he, 'that some woman may repay me. She would then, not only with indifference, but with pleasure, see me united to another; resign me without a pang to some mere common-place insipid piece of sweetness; and give her noble self to one who could better feel her value.'
- 89. De Courcy hadnever declared his preference for Laura; he was even determined not to declare it. Yet to find that she had not even a wish to secure it for herself, gave him such acute vexation, that he was unable to remain in her presence. He abruptly rose and took his leave. He soon however reproached himself with the unreasonableness of his feelings; and returned to his oft-repeated resolution to cultivate the friendship without aspiring to the love of Laura. He even persuaded himself that he rejoiced in her freedom from a passion which could not be gratified without a sacrifice of the most important duties. He had a sister for whom no provision had been made; a mother, worthy of his warmest affection, whose increasing infirmities required increased indulgence. Mrs De Courcy's jointure was a very small one; and though she consented for the present to share the comforts of his establishment, Montague knew her too well to imagine that she would accept of any addition to her income, deducted from the necessary expences of his wife and family. His generous nature revolted from suffering his sister to feel herself a mere pensioner on his bounty, or to seek dear-bought independence in a marriage of convenience, a sort of bargain upon which he looked with double aversion, since he had himself felt the power of an exclusive attachment. Here even his sense of justice was concerned; for he knew that, if his father had lived, it was his intention to have saved from his income a provision for Harriet. From the time that the estate devolved to Montague, he had begun to execute his father's intention; and he had resolved, that no selfish purpose should interfere with its fulfilment. The destined sum, however, was as yet little more than half collected, and it was now likely to accumulate still more slowly; for, as Mrs De Courcy had almost entirely lost the use of her limbs, a carriage was to her an absolute necessary of life. Most joyfully would Montague have sacrificed every luxury, undergone every privation, to secure the possession of Laura; but he would not sacrifice his mother's health nor his sister's independence to any selfish gratification; nor would he subject the woman of his
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