The document discusses various data dissemination protocols in wireless sensor networks. It describes flooding, gossiping, rumor routing, sequential assignment routing, direct diffusion, SPIN, and geographic hash table protocols. Flooding broadcasts packets to all neighbors, causing implosion and resource blindness issues. Gossiping sends packets randomly to one neighbor to avoid implosion. Rumor routing and direct diffusion use flooding initially and then optimize routing. SPIN uses data advertisements before transmission. Geographic hash table hashes node locations to optimize routing.

1. Power Aware Routing protocols
In
Wireless Sensor Networks
BY
DARPAN DEKIVADIYA
09BCE008
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
AHMEDABAD-382481
April 2012

2. Power Aware Routing protocols
In
Wireless Sensor Networks
Seminar
Submitted in partial fulfillment of the requirements
For the degree of
Bachelor of Technology In Computer Engineering
By
DARPAN DEKIVADIYA
09BCE008
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
AHMEDABAD-382481
April 2012

3. Certificate
This is to certify that the Seminar entitled ”Power Aware Routing protocols in Wireless
Sensor Networks” submitted by DARPAN DEKIVADIYA(09BCE008), towards the partial
fulfillment of the requirements for the degree of Bachelor of Technology in Computer Engi-
neering of Nirma University of Science and Technology, Ahmedabad is the record of work
carried out by him under my supervision and guidance. In my opinion, the submitted work
has reached a level required for being accepted for examination. The results embodied in
this Seminar, to the best of my knowledge, haven’t been submitted to any other university
or institution for award of any degree or diploma.
Prof. Jitali Patel Prof. D. J. Patel
Assistant Professor, Professor and Head,
Dept. of Computer Science & Engg., Dept. of Computer Science & Engg.,
Institute of Technology, Institute of Technology,
Nirma University, Ahmedabad Nirma University, Ahmedabad
Prof. Ankit Thakkar
Guide and Assistant Professor,
Institute of Technology,
Nirma University, Ahmedabad
iii

4. Abstract iv
Recent developments in the area of micro-sensor devices have accelerated advances in the
sensor networks field leading to many new protocols specifically designed for wireless sensor
networks (WSNs). Wireless sensor networks with hundreds to thousands of sensor nodes
can gather information from an unattended location and transmit the gathered data to a
particular user, depending on the application. These sensor nodes have some constraints due
to their limited energy, storage capacity and computing power. Data are routed from one
node to other using different routing protocols. There are a number of routing protocols for
wireless sensor networks. This report gives the brieg idea about Routing Protocols in Wireless
Sensor Networks which includes Data Dissemination and Data Gathering Protocols.It also
includes classification and comaparision of these Routing Protocols.
iv

5. Acknowledgements v
I would like to express my heartfelt gratitude to Prof.Ankit Thakkar, Professor in De-
partment of computer science and engineering for her valuable time and guidance that made
the seminar project work a success. Thanking all my friends and all those who had helped
me in carrying out this work. I am also indebted to the library resources centre and interest
services that enabled us to ponder over the vast subject of ”Power Aware Routing protocols
in Wireless Sensor Networks”.
- DARPAN DEKIVADIYA
09BCE008
v

6. Contents
Abstract iv
Acknowledgements v
1 Introduction to WSN 1
2 Classification Of Routing Protocols 3
2.1 Based on Mode of Functioning and Type of Target Applications . . . . . . . 3
2.1.1 Proactive :- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.1.2 Reactive :- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.1.3 Hybrid :- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 According to the Participation style of the Nodes. . . . . . . . . . . . . . . . 4
2.2.1 Direct Communication :- . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2.2 Flat :- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2.3 Clustering Protocols :- . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.3 Depending on the Network Structure . . . . . . . . . . . . . . . . . . . . . . 5
2.3.1 Data Centric :- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.3.2 Hierarchical :- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.3.3 Location Based :- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
3 Data Dissemination Protocols 6
3.1 Flooding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.2 Gossiping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.3 Rumor Routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3.4 Sequential Assignment Routing :- . . . . . . . . . . . . . . . . . . . . . . . . 9
3.5 Direct Diffusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.6 Sensor Protocol for Information via Negotiation . . . . . . . . . . . . . . . . 11
3.7 Geographic Hash Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4 Data Gathering Protocols 13
4.1 Direct Transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.2 Power Efficient Gathering for Sensor Information Systems . . . . . . . . . . 14
4.3 Binary Scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4.4 Chain Based Three level Scheme . . . . . . . . . . . . . . . . . . . . . . . . . 16
vi

7. Chapter 1
Introduction to WSN
A wireless sensor network (WSN) consists of spatially distributed autonomous sensors
to monitor physical or environmental conditions, such as temperature, sound, vibration,
pressure, motion or pollutants and to cooperatively pass their data through the network to
a main location.
The more modern networks are bi-directional, also enabling control of sensor activity.
The development of wireless sensor networks was motivated by military applications such
as battlefield surveillance; today such networks are used in many industrial and consumer
applications, such as industrial process monitoring and control, machine health monitoring,
and so on.
Figure 1.1: Typical multi-hop wireless sensor network architecture
1

8. The WSN is built of ”nodes” from a few to several hundreds or even thousands, where
each node is connected to one (or sometimes several) sensors. Each such sensor network node
has typically several parts: a radio transceiver with an internal antenna or connection to an
external antenna, a microcontroller, an electronic circuit for interfacing with the sensors and
an energy source, usually a battery or an embedded form of energy harvesting.
A sensor node might vary in size from that of a shoebox down to the size of a grain
of dust, although functioning ”motes” of genuine microscopic dimensions have yet to be
created. The cost of sensor nodes is similarly variable, ranging from a few to hundreds of
dollars, depending on the complexity of the individual sensor nodes. Size and cost constraints
on sensor nodes result in corresponding constraints on resources such as energy, memory,
computational speed and communications bandwidth.
The topology of the WSNs can vary from a simple star network to an advanced multi-hop
wireless mesh network. The propagation technique between the hops of the network can be
routing or flooding
2

9. Chapter 2
Classification Of Routing Protocols
Routing techniques are required for sending data between sensor nodes and the base
stations for communication. Different routing protocols are proposed for wireless sensor
network. These protocols can be classified according to different parameters.
ˆ Routing Protocols can be classified as Proactive, Reactive and Hybrid, based on their
Mode of Functioning and Type of Target Applications.
ˆ Routing protocols can be classified as Direct Communication, Flat and Clustering
Protocols, according to the Participation style of the Nodes.
ˆ Routing Protocols can be classified as Hierarchical, Data Centric and location based,
depending on the Network Structure.
2.1 Based on Mode of Functioning and Type of Target
Applications
2.1.1 Proactive :-
In a Proactive Protocol the nodes switch on their sensors and transmitters, sense the
environment and transmit the data to a BS through the predefined route.
e.g. The Low Energy Adaptive Clustering hierarchy protocol (LEACH) utilizes this type
of protocol.
2.1.2 Reactive :-
if there are sudden changes in the sensed attribute beyond some pre-determined threshold
value, the nodes immediately react. This type of protocol is used in time critical applications.
e.g. The Threshold sensitive Energy Efficient sensor Network (TEEN) is an example of
a reactive protocol.
3

10. 2.1.3 Hybrid :-
Hybrid protocols incorporate both proactive and reactive concepts. They first compute
all routes and then improve the routes at the time of routing. e.g. Adaptive Periodic TEEN
(APTEEN) is an example of a reactive protocol.
2.2 According to the Participation style of the Nodes.
2.2.1 Direct Communication :-
In this type of protocols, any node can send information to the Base Station(BS) directly.
When this is applied in a very large network, the energy of sensor nodes may be drained
quickly. Its scalability is very small.
e.g. SPIN is an example of this type of protocol.
2.2.2 Flat :-
In the case of flat protocols,if any node needs to transmit data, it first searches for a valid
route to the BS and then transmits the data. Nodes around the base station may drain their
energy quickly. Its scalability is average.
e.g. Rumor Routing is an example of this type of protocol.
2.2.3 Clustering Protocols :-
According to the clustering protocol,the total area is divided into numbers of clusters.
Each and every cluster has a cluster head (CH) and this cluster head directly communicates
with the BS. All nodes in a cluster send their data to their corresponding CH.
e.g. TEEN is an example of this type of protocol.
4

11. 2.3 Depending on the Network Structure
2.3.1 Data Centric :-
Data centric protocols are query based and they depend on the naming of the desired
data, thus it eliminates much redundant transmissions. The BS sends queries to a certain
area for information and waits for reply from the nodes of that particular region. Since data
is requested through queries, attribute based naming is required to specify the properties of
the data. Depending on the query, sensors collect a particular data from the area of interest
and this particular information is only required to transmit to the BS and thus reducing the
number of transmissions.
e.g. SPIN was the first data centric protocol.
2.3.2 Hierarchical :-
Hierarchical routing is used to perform energy efficient routing, i.e., higher energy nodes
can be used to process and send the information; low energy nodes are used to perform the
sensing in the area of interest.
examples: LEACH, TEEN, APTEEN.
2.3.3 Location Based :-
Location based routing protocols need some location information of the sensor nodes.
Location information can be obtained from GPS (Global Positioning System) signals, re-
ceived radio signal strength, etc. Using location information, an optimal path can be formed
without using flooding techniques.
e.g. Geographic and Energy-Aware Routing(GEAR)
5

12. Chapter 3
Data Dissemination Protocols
Data dissemination is the process by which queries or data are routed in the sensor
network. The data collected by sensor nodes has to be communicated to the BS or to any
other node interested in the data. The node that generates data is called a source and the
information to be reported is called an event. Anode which is interested in an event and
seeks information about it is called a sink. Traffic Models have been developed for sensor
networks such as the data collection and data dissemination (diffusion) models. In the data
collection model, the source sends the data it collects to a collection entity such as the BS.
This could be periodic or on demand. The data is processed in the central collection entity.
Data diffusion, on the other hand, consists of a two-step process of interest propagation and
data propagation. an interested is a descriptor for a particular, intrusion or presence of bio-
agents. For every event that a sink is interested in , it broadcasts its interest to its neighbors
and periodically refreshes its interest. The interest is propagated across the network and
every node maintains an interest cache of all events to be reported.
3.1 Flooding
In Flooding, Each node Which receives a packet broadcasts it, if the maximum hop count
of the packet is not reached and node itself is not the destination of the packet.This technique
does not require complex topology maintenance or route discovery algorithms.
Flooding has Following disadvantages :
ˆ Implosion : This is situation when duplicate messages are sent to the same node.
This occurs when a node recieves coppies of the same message from many of its neigh-
bours.
ˆ Overlap : The same event may be sensed by more than one node due to overlapping
of regions of coverage. this results in their neighbors receiving duplicate reports of the
same event.
ˆ Resource Blindness : The flooding protocol does not consider theavailable energy
at the nodes and results in many redundant transmissions. so,it reduces the network
lifetime.
6

13. 3.2 Gossiping
Gossiping is modified version of flooding, where the nodes do not broadcast apacket, but
send packets to a randomly selected neighbor. This avoids the problem of Implosion.
It takes a long time for a message to propogate throughout the network. Though gossiping
has considerably lower overhead than flooding, it does not guarantee that all nodes of the
network will recieve the message. It relies on the random neighbor selection to eventually
propogate the message throughout the network.
7

14. 3.3 Rumor Routing
Rumor Routing is an agent based path creation algorithm. Agents are long-lived entities
created at random by nodes. These are basically packets which are circulated in the net-
work to establish shortest path to events that they encounter.They can also perform path
optimizations at nodes they visit. When agent finds a node whose path to an event is longer
than its own, it updates the nodes routing table.
Figure 3.1: Rumor Routing
Figure 3.1 illustrates the working of Rumor Routing algorithm. In figure 3.1(a), the agent
has initially recorded a path distance 2 to event E1. Node A’s table shows that it is at a
distance 3 from event E1 and distance 2 from E2. when the agent visits node A, i+t updates
its own path state information to include the path to event E2. The updating is with one
hop greater distance than what it found in A, to account for the hop between any neighbor
of A that the agent will visit next, andA. It also optimizes the path to e1 recorded at node
A to the shorter path through node B. The updated status of the agent and node table is
shown in figure 3.1(b).
When a query is generated at a sink, it is sent on a ranom walk with the hope that it will
find a path leading to the required event. This is based on high probability of two straight
lines intersecting on a planar graph, assuming the network topology is like a planar graph,
and the paths established can be approximated by straight lines owing to high density of the
nodes. If a query does not find an event path, the sink times out and usesflooding as last
resort to propagate the query.
For instance, as in figure 3.1(c), suppose a query for event E1 is generated by node P.
Through a random walk, it reaches A, where it finds the previously established path to E1.
Hence, the query is directed to E1 through node B, as indicated by A’s table.
8

15. 3.4 Sequential Assignment Routing :-
The Sequential Assignment Routing(SAR) creates multiple trees ,where the root of each
tree is a one hop neighbor of sink.Each tree grows outward from the sink and avoids nodes
with low throughput or high delay. At the end of the procedure, most nodes belong to
multiple trees. An instance of tree formation is illustrated in figure.
Figure 3.2: Sequential Assignment Routing
The tree rooted at A and B. Two of the one hop neighbors of the sink are shown. Node
C belongs to bothtrees and has path length of 3 and 5 respectively to the sink, using the
two trees.Each sensor node records two parameters about each path through it:
1. The available energy resources on the path.
2. An additive QoS metric such as delay.
9

16. This allows a node to choose one path from among many to relay its message to the
sink.The SAR chooses a path with the high estimated energy resources and provisions can be
made to accomodate packets of different properties.A wieghted QoS metric is used to handle
prioritized packets which computed as a product of priority leveland delay.The routing esures
that the same weighted QoS metric is maintained.
Thus, higher priority packets take lower delay paths and lower priority packets have to
use the paths of greater delay. e.g. If node C generates a packet of priority 3, it follows the
longer path along tree B, and a packet of priority 5 will follow the shorter path alongtree A.
so that the priority X delay QoS metric is maintained.
SAR minimizes the average weighted QoS metric over the lifetime of the network. The
sink periodically trigers a metric update to reflectthe changes in available energy resources
after some transmissions.
3.5 Direct Diffusion
This potocol is useful in scenario where the sensor nodes themselves generate requests/queries
for data sensed by other nodes, instead of all queries arising only from a BS. Hence the sink
for the query could be a BS or a sensor node. The direct diffusion routing protocol improves
on data diffusion using interest gradients. Each sensor node names its data with one or more
attributes and other nodes express their interest depending on these attributes. Attribute
value pairs can be used to describe an interest in intrusion data as follows.
The sink has to periodically refresh its interest if it still requires the data to be reported
it. Data is propagated along the reverse path of the interest propagation. Each path is
associated with a gradient that is formed at the time of interest propagation. Each path
is associated with the gradient that is formed at the time of interest propagation. While
the positive gradients encourage the data flow along the path, Negative gradients inhibit
the distribution of data along a perticular path. The strength of the interest is different
toward different neighbors, resulting into source to sink paths with different gradients. The
gradient coresponding to an interest is derived from the interval/data-rate field specified in
the interest.
This model uses data naming by attributes and local data transformation to reflect the
data centric nature of sensor network operations. The local operations of Data agreegation
are application-specific gradient model. The network wide results of local interaction by
regulating the flow of data along different paths depending on the expressed interest.
10

17. 3.6 Sensor Protocol for Information via Negotiation
family of protocols for information via negotiation (SPIN) is proposed in [5]. SPIN uses
negotiation and resources and adaption to address the deficiencies of flooding. Negotiation
reduces overlap and implosion, and a threshold based resource-aware operation is used to
prolong network lifetime. Meta-data, or data describing data, is transmitted instead of row
data. This requires fewer bytes and can be in an application-specific format.
SPIN has three types of messages: ADV,REQ, and DATA. A sensor node broadcasts an
ADV containing meta-data describing actual data. If a neighbor is interested in the data ,
it sends REQ for the data. Then the sensor node sends the actual DATA to the neighbor.
The neighbor again sends ADVs to its neighbors and this process continues to disseminate
the data throughout the network. the simple version is shown in figure.
Figure 3.3: Sensor Protocol for Information via Negotiation
SPIN is based on data-centric routing, where the nodes advertise the available data
through an ADV and wait for requests from interested nodes. SPIN-2 expands on SPIN,
using an energy or resource threshold to reduce participation. A node may participate in
the ADV-REQ-DATA handshake only if it has sufficient resources above a threshold.
11

18. 3.7 Geographic Hash Table
Geographic Hash Table is a system based on data centric storage inspired by internet
scale distributed hash table systems such as chard and Tapestry, GHT hashes keys into
geographic co-ordinates and stores a pair at the sensor node nearest to the hash value. The
calculated hash value is mapped onto a unique node consistently, so that queries for the data
can be routed to the correct node. Stored data is replicated to ensure redundancy in case of
node failures and consistently protocol is used to maintain the replicated data. The data is
distributed among nodes such that it is scalable and the storage load is balanced.
GHT is more effective in large network where a large number of events are detected but
not all are queried. In this case data observed is stored in a distributed manner across
all nodes, instead of being routed to central external storage. Queries are routed to the
nearest node which contains a copy of the relevant data. This makes the storage and traffic
distribution uniform.
12

19. Chapter 4
Data Gathering Protocols
The objective of the data-gathering problem is to transmit the sensed data from each
sensor node to a BS. One round is defined as the BS collecting data from all the sensor nodes
once. The goal of algorithms which implement data gathering is to maximize the number of
rounds of communication before the nodes die and the network becomes inoperable. This
means minimum energy should be consumed and the transmission should occur with mini-
mum delays, which are conflicting requirements. Hence, the energy X delay metric is used to
compare algorithms, since this metric measures speedy and energy-efficient data gathering.
A few algorithms that implement data gathering are discussed below.
4.1 Direct Transmission
All sensor nodes transmit their data directly to BS. This is extremely expensive in terms
of energy consumed, since the BS may be very far away from some nodes. Also, nodes must
take turns while transmitting to the BS to avoid collision , so the media access delay is also
large. Hence, this scheme performs poorly with respect to the energy X delay matrix.
13

20. 4.2 Power Efficient Gathering for Sensor Information
Systems
Power Efficient Gathering for Sensor Information Systems (PEGASIS) is a data-gathering
protocol based on the assumption that all sensor nodes know the location of every other node,
that is, the topology information is available to all nodes. Also,any node has the required
transmission range to reach the BS in one-hop, when it is select as a leader. The goals of
PEGASIS are as follows :
ˆ Minimize the distance over which each node transmits.
ˆ Minimize the broadcasting overhead.
ˆ Minimize the number of messages that need to be sent to the BS.
ˆ Distribute the energy consumption equally across all nodes.
14

21. Figure 4.1: Sequential Assignment Routing
A greedy algorithm is used to construct a chain of sensor nodes, starting from the node
farthest from the BS. At each step, the nearest neighbor which has not been visited is added
to the chain. The chain is constructed a priory, before data transmission begins and is
reconstructed when nodes die out. At every node, data fussion is carried out. so, that only
one message is passed on from one node to next. A node which is designated as the leader
finally transmits one message to BS.
Leadership is transffered in sequential order and a token is passed. so that the nodes
know in which direction to pass messages in order to reach the leader. A possible chain
formation is illustrated in figure. The delay involved in message reaching the BS is O(N),
where N is the total number of nodes in the network.
15

22. 4.3 Binary Scheme
This is also a chain-based scheme like PEGASIS, which classifies nodes into different
levels. All nodes which recieve messages at one level rises to the next level.
Step 1 :- S0 → S1 S2 → S3 S4 → S5 S6 → S7
Step 2 :- S1 → S3 S5 → S7
Step 3 :- S3 → S7
Step 4 :- S7 → BS
The number of nodes is halved from one level to the next. For instance,consider a network
with eight nodes labled from S0 to S7. In figure agreegated data reaches the BS in 4 steps
which is O(log2 N ).where N is the number of nodes in the network.
4.4 Chain Based Three level Scheme
For non CDMA sensor nodes, a binary scheme is not applicable. The chain based three
level scheme addresses this situation. In this scheme chain is constructed as in PEGASIS.
The chain is devided into into number of groups to space out simulteneous transmission in
order to minimize interference. Within a group , nodes transmit one at a time.
One node out of each group agreegates data from all group members and rises to the
next level. The index of this leader node is decided priori. In the second level all nodes are
devided into two groups and the third level consist of a message exchange between one node
from each group of second level. Finally the leader transmits a single message to BS.
Step 1 :- S0 → S1....S6 → S7 ← S8 ← S9 S10 → S11....S16 → S17 ← S18..........S97 ←
S98 ← S99
Step 2 :- S7 → S17 ← S27 ← S37 ← S47 S57 → S67 ← S77 ← S87 ← S97
Step 3 :- S17 ← S67
Step 4 :- S67 → BS
The working of this scheme is explain in above figure.Suppose Network has 100 nodes
and the group size is 10 for the first level and 5 for second level. Three levels have been
found to give the optimal energy X delay through simulation.
16

23. References :-
ˆ Ad Hoc Wireless Networks By,C.Shiva Ram Murthy and B.S.Manoj
ˆ www.mdpi.com/jouranal/sensor
ˆ www.wikipedia.org/wiki/Wireless sensor network
17