Final PhD Defense Presentation

Submitted By:
Piyush Charan
Enrolment No. :13001
Date of Enrollment: 11-Oct-2013
Under the guidance of
Supervisor:
Prof. Tahsin Usmani
Dept. of Electronics and
Communication Engg.
Integral University, Lucknow
Co-Supervisor:
Dr. Rajeev Paulus
Dept. of Electronics and
Communication Engg.
SHUATS, Allahabad
A Final Presentation on

I. Introduction
– Motivation
– Hypothesis
– Approved Objectives
– Contributions of the Thesis
II. Literature Survey
III. Design, Simulation & Performance Evaluation
IV. Design of caching framework for IEEE802.15.4 based
WSNs, Performance Analysis and Validation
V. Conclusion and Future Prospects
VI. List of Publications
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Piyush Charan, Enroll No.: 13001

I. Introduction
• Energy efficient routing in wireless networks has been the
subject of intensive study in recent years.
• The IEEE 802.15.4 covers the physical layer and the
MAC layer of LR-WPAN (low rate wireless personal
area network).
• The ZigBee device is “an emerging standard that is based
on the IEEE 802.15.4 and adds network construction (star
networks, peer-to-peer/mesh networks, and cluster-tree
networks), application services, and more”.
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Motivation
• The main motivation to carry out this research in a
WSN scenario is to provide uninterrupted supply of
data with
• Minimal Latency (Cooperative Caching)
• Minimum Number of Packet Overheads (Suitable Routing
Protocol, DEAR)(unnecessary packets processing may be
avoided), and
• Minimum Energy Consumption (Suitable MAC protocol,
Beacon enabled mode of IEEE802.15.4 based nodes). Why
Energy Aware Routing protocol? So that network lifetime
may be enhanced.
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Hypothesis
• Hypothesis Statement: The performance and Quality of Service in IEEE
802.15.4/ZigBee based Wireless Sensor Networks based on the Energy Consumption is
improved when the proposed DEAR protocol is used with cooperative caching scheme over
the standard AODV routing protocol.
• Null Hypothesis (H0): The performance of DEAR routing protocol with CCZ caching
scheme for nodes in IEEE 802.15.4 based WSNs is less than or equal to the standard AODV
protocol when analyzed with the same caching scheme. This also means that the energy
consumption of nodes in a sensor network routing data by the standard routing protocol
AODV with CCZ caching (μ1) is less than or equal to the energy consumption of nodes
routing data by DEAR protocol with CCZ caching (μ2).
• Alternative Hypothesis (HA): The performance of sensor nodes simulated with DEAR
protocol and CCZ caching scheme is better with respect to the standard AODV protocol
when analyzed with the same caching scheme. This also means that the energy
consumption of nodes in a sensor network routing data via the standard AODV protocol
with CCZ caching algorithm (μ1) is greater than the energy consumption of nodes routing
data by DEAR routing protocol with CCZ caching (μ2).
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Approved Research Objectives
The objectives of this research work is as follows:
• To study the various MANET routing protocols.
• To evaluate the performance of AODV routing protocol in IEEE 802.15.4/ZigBee
based Wireless Sensor Networks for 16 nodes.
• To study the literature on Cooperative Caching.
• To develop a routing protocol (i.e. DEAR protocol) for energy efficient routing
using cooperative caching in IEEE 802.15.4/ZigBee based Wireless Sensor
Networks
• The Quality of Service (QoS) of the proposed DEAR algorithm with CCZ
Cooperative Caching Scheme is evaluated on some performance metrics. These
metrics are Average Query Latency, Byte Hit Ratio and the overall Energy
consumption of the network
• Performance analysis based on Energy efficiency and Reliability is accomplished
for larger ubiquitous sensor networks based on the IEEE802.15.4 MAC and PHY
standards.
• Empirical Validation for Energy efficiency of DEAR routing protocol over AODV
in IEEE802.15.4 based Wireless Sensor Networks.
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Contributions of Thesis
1. WSN consisting of nodes based on IEEE 802.15.4 standard has been
implemented with Adhoc on-demand distance vector (AODV) routing protocol
and the performance is evaluated based on the following performance metrics:
Throughput, end-to-end delay, average jitter and energy consumption.
2. Distributed Energy Aware Routing (DEAR) protocol for Wireless Sensor
Networks proposes an energy aware routing protocol for WSNs based on IEEE
802.15.4 MAC and PHY standards is used with a localized algorithm CCZ that
retrieves data from the caching nodes.
3. Caching in Cooperative Zones (CCZ) is a localized algorithm that is used with
AODV and DEAR routing protocols separately to reduce the overall energy
consumption of the wireless nodes by retrieving required datum from the nearby
caching node.
4. Performance analysis based on Energy efficiency and Reliability is accomplished
for larger ubiquitous sensor networks based on the IEEE802.15.4 MAC and PHY
standards.
5. Empirical Validation for Energy efficiency of DEAR routing protocol over AODV
in IEEE802.15.4 based Wireless Sensor Networks.
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II. Literature Survey
Authors Year Wireless Technology Proposed Design Inference/ Specific Contribution
F.L. Lewis et al., 2004 IEEE 802.11 Survey on WSNs and
it types.
 Wireless Sensors are a boon to the
society as they lead to the
development of smart environments.
 current topic of research is active
power control
1. K. Prashant et al.,
2. Naveen Chauhan
et al.
2010
2011
IEEE802.11 proposed a
cooperative caching
strategy in MANETs
(Mobile AdHoc
Networks) that was
based on Clusters
• It also proposed that Cooperative
caching helps MANETs in alleviating
from the situation of non data
availability.
• This algorithm completely exploited
the Pull Mechanism to facilitate cache
sharing in a MANET. It supported
efficient data retrieval in ad hoc
networks.
K. Wu et al., 2010 IEEE802.11 proposed an
algorithm for Cluster
Head Selection and
update for adhoc
networks
 reduced the total number cluster
overheads and cluster change events.
Hence its QoS (Quality of Service) was
improved
P. Kuppuswamy et al 2011. IEEE802.11 proposed a review on
cooperative caching
strategies in
MANETs.
They concluded that using cooperative
caching in ad hoc networks the delay time
and the number of packet overheads may
be reduced.
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Literature Survey
Nikos Dimokas et al. 2008 IEEE802.11 proposed a cooperative
caching protocol for
Wireless Multimedia
Sensor Networks
(WMSNs)
Their algorithm design included the
capabilities to locate the cached data and
provided a purging out facility for the
cache.
T. P. Sharma et al. 2008 IEEE802.11 proposed a dual radio
based cooperative caching
scheme for wireless sensor
networks.
Simulation results show that the proposed
caching mechanism when applied to two-
tier data dissemination (TTDD) and the
proposed dual radio based data
dissemination (DRDD) performs better
and show significant energy efficiency as
compared to scenarios when caching is not
employed.
Nikos Dimokas et al. 2009 IEEE 802.11 described a high
performance and less
complicated cooperative
caching strategy for
Wireless Sensor Networks
Their algorithm serves data request with
less latency and minimal energy
consumption for several applications such
as controlling smart buildings.
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Literature Survey
P. Anitha et al., 2011 IEEE802.15.4 proposed an algorithm for
IEEAODV (Improved
Energy Efficient Adhoc On
Demand Distance Vector)
Routing Protocol for ZigBee
devices.
selects the maximum suitable path
between source and destination on the
basis of energy of nodes, stability of nodes
and hop-count of paths.
when a node receives a R-RREQ message
then it first compares its Energy with
Energy of R-RREQ packet. After assigning
the priorities to paths Source will select the
path having higher priority, if this path
breaks then next higher priority path will
be selected.
Kavita Malav et al., 2015 IEEE802.15.4 reviewed the various
Energy Efficient Routing
Protocols in Zigbee
Wireless Sensor Networks.
They discussed about the
Negotiation based
protocols, Multipath based
Protocols, and Query based
Protocols.
 discussed the Beacon based conflicts
in a ZigBee Tree Network.
 have discussed the design of IEEE
802.15.4 and ZigBee Network layer
protocols
Prativa P. Saraswala 2013 IEEE802.15.4 has discussed the various
types of Routing Protocols
that are employed in
ZigBee Network.
She has also discussed about the metrics
on which the performance of the network
will be analyzed.
They have discussed the Network nodes
and the topology supported by IEEE
802.15.4/ ZigBee Standard.
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Fig.1 WSN and its Applications
Pic Credit: “Wireless Sensor Networks”, by F.L. Lewis , University
of Texas, 2004
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IEEE 802 Wireless Space
Fig.2. IEEE 802 wireless Network Groups based on data rates. [Adapted from: Alam, M.M. et al. (2014)]
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ZigBee Protocol Stack versus OSI
Model
Fig.3. ZigBee Protocol Stack
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Features of ZigBee
 Works in the Universal ISM band of 2.4 GHz
 And the data rate is 250kb/s
 Standards based and governed by IEEE
 Low cost
 Can be used globally
 Reliable and self healing
 Supports large number of nodes
 Easy to deploy
 Very long battery life
 Secure
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Parameter Specification
Data rate 250 kbps
Number of channels 16
Operating frequency 2.4GHz
Channel spacing 5 MHz
Spread spectrum Direct Sequence Spread
Spectrum (DSSS)
Chip rate 2 Mega chips per second.
Modulation OQPSK with Half sine pulse
shaping
Table 1: ZigBee Specifications
Specifications of ZigBee Devices
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Caching
• Caching is a technique where
frequently accessed data items
that have already been used or
requested by the application
are generally stored closer to
the requester than to the
original source for later reuse.
• Cache is the frequently
accessed data items at devices
to improve performance of
database queries and
availability of data items for
query.
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Fig.4. Typical ZigBee based Wireless Sensor Network
Back
III. Design, Simulation and
Performance Evaluation

Cooperative Caching
• In cooperative caching-
• A typical sensor node stores the data in its on-
board cache memory so that it is served to the
requester when a query is made. Such a node in
this case is known as a caching node.
• The CN, not only serves its own data requests but
also the requests from neighboring nodes.
• A CN, not only stores data for its own needs but
also for other neighboring nodes.
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Need of Caching
• Shorter path, less expensive links, less conflicts, lower risks
of route breakage.
• Saves time, energy and bandwidth consumption as well as
improves data availability.
• Data locality and commonality in interest of users.
• Users/nodes around the same location tend to have similar
interests.
• Soldiers in the battle field: enemy information, target.
• Vehicular ad hoc network: traffic, accident, weather.
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Fig.5. Typical data request handling by Caching in Cooperative Zones (CCZ) Algorithm
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AODV
• The source node sends
the route request
(RREQ) data packet in
the entire network.
• Each node in the
network pushes the
RREQ data frame to its
next one -hop neighbor
that has been receive
by the Source node or
its one hop neighbor.
• This process is called
Flooding.
9
5
7
8
6
2
4
3
1
Destination
Source
RREQ
Fig. 6 The route request (RREQ) flooding
for route discovery
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AODV contd…
• The destination or the
intermediate node, which
has a valid route towards
the destination, answers
with a RREP (Route
Reply) unicast packet as
shown in figure
• The data is sent to the sink
node or destination via the
route discovered by the
RREP messages.
9
5
7
8
6
2
4
3
1
Destination
Source
RREP
Fig.7 The route reply (RREP) unicast for route
discovery
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AODV contd…
If the data frame gets
damaged or lost in the
middle of the routing path
then Then a Route Error
(RERR) message is
propagated to the source
thereby indicating to
resend the lost data frame.
Fig.8 The route maintenance stage in AODV
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DEAR Protocol
• The DEAR protocol is an energy aware routing protocol.
• The Distributed Energy Aware Routing algorithm is an
extension to the conventional AODV routing algorithm
for MANETs.
• The route discovery process in DEAR is different from
AODV.
• A node is accepted in a route only when the total energy
cost TEC is greater than the threshold value.
• The threshold value is 80% of the average link cost.
• DEAR protocol is expected to minimize the overall cost
of power consumption while satisfying the requested
QoS.
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• The link cost is the most important feature of a
Wireless Sensor Node/Mote in a Network.
• Let us assume that there are ‘i’ number of nodes .
• Each Node is associated with say ‘Ti’ traffic in
packets per second (pps).
A
C
B
D
E
Source
Node:
ZigBee End
Device->
It Could be
any sensor.
Sink Node:
ZigBee
Coordinator
2
4
2
5 6
Here , B, C, and D
are ZigBee Routers
Fig.9 WSN Scenario with various Link Cost for five nodes
Explanation of Link Cost
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• Let us assume that a data flow ‘l’ carries a data
traffic at a rate of ‘Tl’ pps.
• Then ‘Ti’ can be estimated as:
• ………..(1)
• Where;
• D(i) denotes the set of data flows through the node ‘i’
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• The two important metrics of any node/motes (in
this case based on IEEE 802.15.4/ZigBee)are:
– (1). Power Consumption and,
– (2). QoS (Quality of Service)
• Let Pi(T) and Qi(T) be the power requirement and
QoS requirement of a particular node ‘i’ in the
network when it carries T(pps).
• If a new stream of data, ‘m’ is added to node i
then this will result in a change in power
consumption and QoS at that node.
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• Assuming that pi(T) be the instantaneous power
consumption by the i-th node when it carries ‘T’ packets
per second that includes all aspects of packet processing:
storing, routing and forwarding them through neighboring
nodes.
• We now define the ‘Total Power Cost’ associated with the
m-th flow as following:
....(2)
Power consumption
due to the m-th flow
The effect of m-th flow on other
flows in process in the i-th node
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• Where ;
• a, b≥0
• 1st term represents total power in watts due
to addition of m-th flow, multiplied with some
constant ‘a’.
• 2nd term represents the increase in wattage
for the other flows associated with the i-th
node, multiplied by some constant ‘b’
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• Hence, the total power cost functions for the m-th
traffic flow rate ‘tm’ on a path ‘λi’ starting from
node ‘i’is written as:
…….(3)
• Similarly the QoS criterion, such as loss, delay or
Packet Delivery Ratio is given by-
…….(4)
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• Where;
• In which  1≤j≤[ ]
• Also = i –th node
• Represents the successive nodes of path λ(i)
• Now total link cost is:
Link Cost= Power Cost + QoS Cost….. (5)
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• Therefore,
…….(6)
• Where;  represents the Total Link Cost
• We have optimize the link cost in equation (6)
then we can achieve an Energy Efficient
Algorithm for Distributed Wireless Sensor
Network based on IEEE 802.15.4
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Fig.10. Flowchart for
DEAR Protocol
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Algorithm for DEAR protocol
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Performance Metrics
• To evaluate the performance of the
proposed DEAR routing protocol with the
CCZ caching algorithm the following
performance metrics are considered:
– Average Query Latency
– Byte Hit Ratio (B)
– Total Energy Consumption
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Proposed Star/Cluster Network
Model
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Fig.11. Star based network

Proposed Grid Network Model
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Fig.12. Grid based network

IV. Design of caching framework
for IEEE802.15.4 based WSNs,
Performance Analysis and
Validation
Back
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Simulation Parameters
• The following parameters have been used
in the simulation setup.
Parameter Default Value Range
Number of Nodes 16 100~200
Number of Data Items 500
Payload Size 64bytes
PHY and MAC Layer IEEE802.15.4
Channel Frequency 2.4GHz
Bandwidth (kbps) 250
Waiting interval (tw) 10s
TTL 300s 100~300s
Cache Size (KB) 800 200~1400
Traffic Type CBR
Routing Protocol AODV/DEAR
Beacon Order 3
Superframe Order 2
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AODV Routing Protocol
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Energy Consumption v/s Data Rate
for Star Connected Network
Data
Rate
AODV
AODV with CCZ
caching algorithm
pps mWh mWh
1 2.900 2.751
2 3.001 2.692
3 3.300 2.628
4 3.391 2.625
5 3.350 1.452
6 3.388 2.429
7 3.419 2.031
Inference:
AODV with CCZ caching algorithm shows minimized energy consumption
as compared to when CCZ is not used and the network is simulated using
AODV only.
A dip in Energy Consumption is noted when the data rate is 5pps. It is
that instance where the data requested is retrieved from the local cache.
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Energy Consumption v/s Data Rate for
Grid Connected Network
Data
Rate
AODV
AODV with
CCZ caching
algorithm
pps mWh mWh
1 2.791 2.221
2 2.803 1.980
3 3.103 1.871
4 3.280 1.794
5 3.310 1.742
6 3.412 1.785
7 3.454 1.790
Inference:
AODV with CCZ caching algorithm shows minimized energy consumption as
compared to when CCZ is not used and the network is simulated using AODV only.
CCZ is showing an improved performance in terms of the Energy Consumption by
the Network. A continuous decrease in energy consumption is seen upto 5pps and
rises slightly beyond. Back

Average Query Latency v/s Cache Size
Cache
Size
Star
Connected_AODV
_CCZ
Grid
Connected_AODV
_CCZ
KB ms ms
200 85 72
400 78 60
600 64 58
800 60 50
1000 58 46
1200 56 43
1400 54 41
Inference:
The simulation reveals that the average query latency decreases with increase in
Cache Size as more number of requests is satisfied.
This is due to the fact that more required data items can be found in the local
cache as the cache size increases. The average query latency in the Grid/Peer-to-
Peer Connected Network is less as compared to the Star/Cluster Based Network.
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Byte Hit Ratio v/s Cache Size
Cache
Size
(KB)
Star
Connected_AO
DV_CCZ
Grid
Connected_AODV
_CCZ
200 0.5 0.6
400 0.6 0.7
600 0.7 0.8
800 0.75 0.85
1000 0.8 0.87
1200 0.82 0.88
1400 0.84 0.88
Inference:
When the cache size is small then data is contributed more by zone hit and remote hit
but as soon as we increase the cache size the contribution by local hits become
significant. This is because more number of data items are found in the local cache as
the cache gets larger.
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DEAR Routing Protocol
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Energy Consumption v/s Data Rate
for Star Connected Network
Inference:
DEAR with CCZ caching algorithm shows minimized energy consumption as
compared to when CCZ is not used and the network is simulated using DEAR only.
For the Star/Cluster network with DEAR routing protocol, the average node
energy consumption is 2.45 mWh. However, when DEAR routing protocol and
CCZ cache algorithm are used together, the average energy consumption is
1.64mWh.
Data
Rate
DEAR DEAR with CCZ
caching
algorithm
pps mWh mWh
1 2.042 1.937
2 2.084 1.871
3 2.276 1.812
4 2.354 1.822
5 2.602 1.392
6 2.826 1.355
7 3.017 1.312
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Energy Consumption v/s Data Rate for
Grid Connected Network
Inference:
DEAR with CCZ caching algorithm shows minimized energy consumption as compared to
when CCZ is not used and the network is simulated using DEAR only.
For a Grid Network, the average energy consumption by nodes with only DEAR routing
algorithm was 2.41 mWh. And when DEAR routing protocol is used with the CCZ caching
algorithm then the average energy consumption is 1.14 mWh
Data
Rate
DEAR DEAR with CCZ
caching algorithm
pps mWh mWh
1 1.831 1.217
2 1.904 1.154
3 2.215 1.061
4 2.448 1.102
5 2.786 1.087
6 2.813 1.118
7 2.885 1.234
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Average Query Latency v/s Cache Size
Cache
Size
Star
Connected_DE
AR_CCZ
Grid
Connected_DEAR_
CCZ
KB ms ms
200 73 62
400 65 52
600 61 50
800 51 45
1000 48 39
1200 46 35
1400 43 31
Inference:
The average query latency (Tqavg) decreases as the size of the cache increases, since both
cases satisfy more number of data queries. This is because as the size of the cache increases,
more of the required data items can be found in the local cache. Average query latency in
grid/peer-to-peer networking is less than in star / cluster based networks.
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Byte Hit Ratio v/s Cache Size
Inference:
•The graph shows the impact of varying cache size on byte hit ratio. Both the Star Connection
Network and the Grid Connection Network show better byte hit rates as the size of the cache
increases. When the cache size is small, the data is more contributed by zone hits and remote hits,
but as the cache size is increased, the contribution of local hits becomes significant.
•According to the simulation results, the grid connection network has better byte hit ratio than the
star / cluster connection network.
Cache
Size
(KB)
Star
Connected_DEAR_
CCZ
Grid
Connected_DEAR_
CCZ
200 0.68 0.75
400 0.75 0.8
600 0.83 0.85
800 0.88 0.90
1000 0.9 0.92
1200 0.92 0.95
1400 0.95 0.98
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Reliability And Energy
Efficiency Analysis For Large
Networks Based On
IEEE802.15.4
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Reliability
• Reliability refers to the successful transmission of
data in the form of bundles from one end of the
wireless sensors that are from the Sensors (or
source node) to the other end of the network that
is to the PAN Coordinator (or sink node)
• Achieving reliability with cooperative caching is
challenging because sometimes the data requested
by the sink node in the pull mode is procured from
the nearby caching node but that data is not
reliable due to the fact that its time-to-live (ttl)
value may have expired.
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Reliability contd.
• So, reliability is an important issue that
needs to be addressed as it also provides a
trade-off between efficient energy
consumption and the successful delivery of
the datum requested by the requester node
or the sink node.
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Simulation Scenarios
• Three scenarios have been considered in which we consider
two analytical models for the simulation of nodes and one
random model.
• The two analytical models are previously discussed :
– The Star/Cluster based model.
– The Grid/Peer-to-Peer based model.
• A random model is also considered as the third network
scenario wherein the motes are deployed randomly as shown
below in fig. 4.11. These IEEE802.15.4 based wireless nodes
are randomly deployed in an area of 100m *100m.
• The number of motes is varied from 100 nodes to 200 nodes
and the simulation is modeled for Distributed Energy Aware
Routing (DEAR) protocol with CCZ cooperative caching as
data retrieval model.
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Random Model: The motes are
deployed randomly
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• Table 11. Reliability in terms of Byte Hit Ratio (B) in each scenario based on the
number of nodes with DEAR protocol and the CCZ caching algorithm.
No. of Nodes Byte Hit Ratio (in %age)
Scenario 1-
Randomly Deployed
Network
Scenario 2- Star
Based Model
Scenario 3- Grid
Based Model
100 100 100 100
120 100 100 100
140 100 99.2126 98.7261
160 98.7842 96.1877 98.3003
200 99.6497 100 99.0923
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The simulation results clearly show that when the number of nodes is increased in the
network then for the Star Based network the Byte hit ratio (BHR) drops to nearly 96% at
160 nodes which is still a good percentage.
Fig.4.12. Graph
showing the
Reliability in
terms of Byte Hit
Ratio exhibited in
different Network
Scenarios for
DEAR protocol
with Caching v/s
the number of
nodes
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• However, when we compare this with other network
topologies then star based or cluster based network loses its
sheen.
• The randomly deployed nodes show better and consistent
reliability in terms of the byte hit ratio even when the number
of nodes is increased. The drop in the percentage of BHR in all
the three scenarios shows that when the number of nodes is
increased the packet drops increases slightly.
• When we compare these results with the results of S.
Gowrishankar et al. (2009) in which they estimated the
reliability in terms of the packet delivery ratio (PDR) there is
an increase of nearly 20% in the reliability exhibited by the
proposed system with cooperative caching, wherein the pull
mode scenario of the nodes exploits the cache memory
available on the on-board sensor module for retrieving the
data required to be fetched by the PAN coordinator.
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No. of
Nodes
Energy Consumption (mW)
Scenario 1- Randomly
Deployed Network
Scenario 2- Star
Based Model
Scenario 3- Grid
Based Model
100 4.0205 4.1657 4.0045
120 4.1342 4.1789 4.0879
140 5.4444 4.4759 4.4629
160 4.6610 4.7451 4.6164
200 5.2827 5.0673 4.9405
Table 12. Energy Consumption for different Network Scenarios
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Fig. Graph showing
the Reliability in
terms of Byte Hit
Ratio exhibited in
different Network
Scenarios for DEAR
protocol with
Caching v/s the
number of nodes
The graph clearly shows that the energy consumption in case of the randomly
deployed nodes is higher than the other two analytical models. The average energy
consumption for randomly deployed nodes is 4.7086mW. The star or cluster based
network model exhibits a average energy consumption of 4.5266mW. Whereas, the
peer-to-peer or grid based network exhibits an average energy consumption of
4.4224mW. This shows that a grid based network exhibits lesser energy consumption.
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Empirical Validation of the
Proposed CCZ Model
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Data Set for Empirical Validation
Data Rate
AODV_CCZ
(Energy Consumption when AODV
with CCZ cooperative caching is
used)
DEAR_CCZ
(Energy Consumption when DEAR
with CCZ cooperative caching is
used)
pps mWh mWh
1 2.221 1.217
2 1.980 1.154
3 1.871 1.061
4 1.794 1.102
5 1.742 1.087
6 1.785 1.118
7 1.790 1.234
Table 4.14:
Data Set for
Paired Sample
t-Test for
Energy
Consumption in
IEEE 802.15.4
grid based
network model
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Hypothesis Testing
• The Hypothesis framed in thesis is
validated by performing a two tailed t-test.
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Two tailed t-test
• A two tailed t-test is performed on data.
• This is done so as to assign half of the
alpha to test statistical significance in one
direction and the other half of alpha to test
statistical significance in the other
direction, where alpha (α = 0.05) when
95% level of significance is considered.
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Description of Paired Sample Data
Set for two tailed t-Test
Sample
Size
N
Mean
M
Standard
Deviation
SD
Standard Error
for Mean
SE
AODV_CCZ 7 1.88329 0.16825 0.06359
DEAR_CCZ 7 1.13900 0.06574 0.02485
Difference 7 0.74429 0.14752 0.05575
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Energy
Consumption
in
Peer-to-Peer
Network
(mWh)
DEAR_CCZ
AODV_CCZ
2.2
2.0
1.8
1.6
1.4
1.2
1.0
Boxplot of AODV_CCZ, DEAR_CCZ
Box Plot for the Sampled Data of Energy
Consumption for AODV_CCZ and
DEAR_CCZ
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t-Test: Paired Two Sample for Means of
AODV_CCZ and DEAR_CCZ obtained on
MinitabV14
AODV_CCZ
μ1
DEAR_CCZ
μ2
Mean 1.8833 1.1390
Variance 0.0283086 0.0043220
Observations 7 7
Pearson Correlation 0.491252706
Hypothesized Mean Difference 0
df 6
t Stat 13.35
P(T<=t) one-tail 0.00001
t Critical one-tail 1.943
P(T<=t) two-tail 0.000011
t Critical two-tail 2.447
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t-Test: Paired Two Sample for Difference of
Means of AODV_CCZ and DEAR_CCZ
obtained in Analysis Toolpak of Excel 2013
Data rate AODV_CCZ DEAR_CCZ Difference
pps mWh mWh
1 2.221 1.217 1.004
2 1.98 1.154 0.826
3 1.871 1.061 0.81
4 1.794 1.102 0.692
5 1.742 1.087 0.655
6 1.785 1.118 0.667
7 1.79 1.234 0.556
sample mean 0.7443
sample std deviation (s) 0.147523
Hypothesized Mean difference 0
Sample Size, n 7
Degrees of Freedom, df=n-1 6
t-Stat 13.35
p-value 0.000011
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Since, tstatistical > tcritical, therefore we reject the null hypothesis (H0) and we may
accept the alternative hypothesis (HA). It means that the energy consumption of
nodes in a sensor network routing data via the standard AODV protocol with CCZ
caching algorithm (μ1) may be greater than the energy consumption of nodes
routing data by DEAR routing protocol with CCZ caching (μ2).
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V. Conclusion and Future Scope
• The simulation results for the IEEE 802.15.4 based network when simulated
with distributed energy aware routing (DEAR) protocol and is accompanied
with CCZ cooperative caching scheme show improved-
– Energy Efficiency
– Byte Hit Ratio
– Average Query Latency
• Peer-to-Peer or Grid based network model offer better energy efficiency and
QoS as compared to star or cluster based network model.
• Later, the proposed system is validated by using statistical techniques. A paired
sample two tailed t-test is applied to validate the hypothesis. Thus, the main
contribution of this work is enhanced energy efficiency while taking care of the
QoS.
Back
7/16/2020 69

Future Scope
• The Smart Sensor Networks may provide real cost and efficiency
benefits to the agriculture sector. Potential applications include
water related saving through smart irrigation with features like soil
analysis, monitoring crop conditions to maximize yield, tracking
livestock health and location, and providing real-time local weather
information.
• Keeping all this, we presume that there is still scope for future
work that is listed below:
1. The proposed model may be analyzed for large number of wireless
nodes.
2. The proposed model may be implemented in hardware for real world
applications like the Agriculture sector.
3. The proposed model may be implemented for scenarios wherein
heterogeneous type of data is available like Humidity, Temperature,
Image, and/or Video Signal.
4. The proposed model may be added with additional feature and
functionalities to enhance the Quality of Service (QoS).
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• Piyush Charan, Tahsin Usmani and Syed Hasan Saeed, “A Comprehensive Study
of various on demand Routing Protocols in MANETs”, International Journal of
Electronics and Communication Engineering, Vol. 4 Issue 2, February’2015.
• Piyush Charan, Tahsin Usmani, Rajeev Paulus, Syed Hasan Saeed, “Performance
Evaluation of AODV Protocol for Energy Consumption and QoS in IEEE 802.15.4
Based Wireless Sensor Network Using QualNet Simulator”, Wireless Sensor
Network, Vol.8 Issue 8, 166-175, doi:10.4236/wsn.2016.88014, August’2016.
• Piyush Charan, Tahsin Usmani, Rajeev Paulus, Syed Hasan Saeed, “Cooperative
Caching in IEEE 802.15.4 based Wireless Sensor Networks”, International Journal
of Applied Engineering Research (SCOPUS), Vol.12 Issue 21, 11409-11416,
November’2017. MCN Number: IU/R&D/2017-MCN000206.
Back
7/16/2020 71

• Piyush Charan, Tahsin Usmani, Rajeev Paulus, Syed Hasan Saeed, “A Cooperative
Cache management scheme for IEEE 802.15.4 based Wireless Sensor Networks”,
International Journal of Electrical and Computer Engineering (SCOPUS), Vol.8 Issue
3, 1701-1710, June’2018.
• Piyush Charan, Tahsin Usmani, Rajeev Paulus, Syed Hasan Saeed, “Performance of
Distributed Energy Aware Routing (DEAR) Protocol with Cooperative Caching for
Wireless Sensor Networks”, Wireless Sensor Network, Vol.11 Issue 3, 35-45,
doi:10.4236/wsn.2019.113003, March’2019.
• Piyush Charan, Tahsin Usmani, Rajeev Paulus, Syed Hasan Saeed, “Empirical
Validation for Energy Efficiency of DEAR routing protocol over AODV in
IEEE802.15.4 based Wireless Sensor Networks”, International Journal of Innovative
Technology and Exploring Engineering (SCOPUS), Vol.8 Issue 8, 853-857, June’2019.
• Piyush Charan, Tahsin Usmani, Rajeev Paulus, Syed Hasan Saeed, “Reliability and
Energy Efficiency of DEAR protocol with Cooperative Caching in IEEE802.15.4 based
large ubiquitous Wireless Sensor Networks”, International Journal of Engineering and
Advanced Technology (SCOPUS), Vol.9 Issue 2, 2140-2145, December’2019
7/16/2020 72

References
• [1] Lewis, F. L., “Wireless Sensor Networks”, Smart
Environments: Technologies, Protocols, and Applications
edited by Cook, D.J. and Das, S.K., John Wiley, New York,
USA, 2004
• [2] Chauhan, N., Awasthi, L.K., Chand, N., Joshi, R.C.,
Mishra, M., “A cooperative caching strategy in mobile ad
hoc networks based on clusters”. ACM, 978-1-4503-0464-
1/11/02, pp: 7-20, 2011.
• [3] Prashant, K., Chauhan, N., Awasthi, L.K., Chand, N.,
“Proactive approach for cooperative caching in mobile adhoc
networks”. International Journal of Computer Science 7:
2010, pp: 21-27.

References contd…
• [4] Wu, K., Hanzo, L., Zhong, Z., “A Cluster-head selection and
update algorithm for ad hoc networks”, IEEE Globecom, 2010.
• [5] Kuppusamy, P., Thirunavukkarasu, K. Kalaavathi, B., “Review
of cooperative caching strategies in mobile ad hoc networks”.
International Journal of Computer Applications, 2011.
• [6] P. Anitha and Dr. C. Chandrasekar, “Energy Aware Routing
protocol for ZigBee Networks”, Journal of Computer Applications
(JCA), pp. 92-94, Vol 4, Issue 3, 2011.
• [7] Iman M. AlMomani, Maha K. Saadeh, “FEAR: Fuzzy-Based
Energy Aware Routing Protocol for Wireless Sensor Networks”,
International Journal of Communications, Network and System
Sciences, Scientific Research, Vol. 4, 2011.

References contd…
• [8] Kavita Malav, Deepak Gupta and Vernon Murray, “Energy
Efficient Routing in Zigbee Wireless Sensor Network- A
Review”, International Journal of Advanced Research in
Computer and Communication Engineering, Vol.4 , Issue 4,
April 2015.
• [9] Prativa P. Saraswala, “A Survey on Routing Protocols in
ZigBee Network”, International Journal of Engineering, Science
and Innovative Technology (IJESIT), Vol. 2, Issue 1, Jan 2015.
• [10] Mohammad Rezaeirad, Muhammad Aamir Iqbal, Dmitri
Perkins and Magdy Bayoumi, “Investigating the Feasibility of
LEAP+ in ZigBee Specification”, IEEE International
Conference on Information Reuse and Integration (IRI), pp:
406-412, Aug 2014.

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