Network lifetime plays an integral role in setting up an efficient wireless sensor network. Coverage in a network needs to guarantee that the region is monitored with the required degree of reliability. Locations of sensor nodes constitute the basic input for the algorithms that examine coverage of the network. Coverage problems can be broadly classified as area coverage problem and target coverage problem. Area coverage focuses on monitoring the entire region of interest, whereas target coverage concerns monitoring only certain specific points in a given region. Target coverage can be categorized as simple coverage, k-coverage and Q-coverage. Lower coverage level (simple coverage) is enough for environmental or habitat monitoring or applications like home security. Higher degree of coverage (k-coverage) will be required for some applications like target tracking to track the targets accurately, or if sensors work in a hostile environment such as battle fields or chemically polluted areas. More reliable results are produced for higher degree of coverage which requires multiple sensor nodes to monitor the region/targets. An example of Q-coverage is video surveillance systems deployed for monitoring hostile territorial area where some sensitive targets like a nuclear plant may need more sensors cooperate to ensure source redundancy for precise data. Sensor nodes deterministically deployed by using artificial bee colony algorithm, so as to achieve the required target coverage level and maximize the network lifetime.

1. Energy Efficient Node Deployment for Target
Coverage in Wireless Sensor Network
Prepared By : Gaurang Rathod
ME EC Gujarat Technological University
Gujarat India
29 January 2015 rathodgaurang@hotmail.com

2. Outline
 Motivation
 Introduction
 Network Lifetime for Target Coverage
 ABC Algorithm
 Simulation Work
 References

3. Motivation
 Wireless sensor network is energy constrain
network
 Energy consumption of Node[1]
1. Data transmission
2. Signal processing
3. Hardware operation

4. Target Coverage
 Coverage can be classified as area coverage
and target(point) coverage[6]
(a) Area coverage and (b) Point coverage

5. Continue…
 Target Coverage can be categorized
1. Simple coverage
2. k-coverage
3. Q-coverage:
Target T= {T1,T2,..,Tn} should be monitored by
Q= {q1, q2,…, qn} number of nodes

6. Network Lifetime
 Network is live till all targets being sensed
by nodes otherwise network considered as
dead.
 Network life is defined by target sensed time
duration by nodes.
 Deploy nodes such a way that target
sensed by maximum number of nodes, so
network live long.

7. Node Deployment Algorithm
 Input: no. of nodes and no. of target
 Output: optimum location of node such that maximum
network life achieve with required target coverage level
 Procedure
1. Select random location for the given no. of target.
2. Deploy nodes randomly such that each target must be
covered by minimum one node.
3. Compute life time of network.
4. Recomputed node position using ABC algorithm such
that network life maximum.

8. Network Lifetime Calculation
 Let sensor nodes : {s1, s2, s3,…,sm}
randomly deployed to cover the region R with
n targets : {T1,T2,..,Tn}
 Each node has initial energy E0 and a sensing
radius sr
 A sensor node is said to cover target if distance
between node and target is less than radius sr
 Coverage Matrix is defined as
1
0
i j
i j
if S monitorsT
M
otherwise

 


9. Continue…

where ei is energy consumption rate of i-node

 For k-coverage, qj=k, j=1,2,…,n
0
( ) , 1Lifeof node i
i
E
b i m
e
  
1
*
minNetworklifetime
m
i j i
i
j
M b
j q

 
 
 
 

10. Artificial Bee Colony Algorithm[10]
 The colony of artificial bees contain three group
of bees
1. Employed bees
2. Onlookers
3. Scouts
 Employed bees determine a food source within
the neighborhood of the food source in their
memory
 Employed bees share information with
onlookers within the hive and then the
onlookers select one of the food sources

11. Continue…
 Onlookers select a food source within the
neighborhood of the food sources chosen by
themselves
 An employed bee of which the source has been
abandoned becomes a scout and starts to
search a new food source randomly

12. ABC Algorithm Flow Chart

13. Continue..
Image source:
http://commons.wikimedia.org/wiki/File:Maxima_and_Minima.svg

14. Continue…
 New search position
i=bee index
j=random selected dimension
i.e. either x-yam or y-yam random selected
k=random selected bee (k never equal to i)
, , , ,( )i j i j i j k jv x x x   

15. Simulation
A. Target Coverage
B. Importance of Deployment and
Scheduling

16. Experiment Work A
1. For fix number of targets and varying number
of nodes
2. For different-different number of targets and
nodes
3. For changing size of network
4. By varying sensing range of node

17. Simulation Parameters
Parameter Value
Network area 400m x 400m
500m x 500m
Node sensing range 75m
80m
Initial energy 100 J
Energy consumption rate 1 J/S
No. of target 20 to 40
No. of nodes 100 to 250

18. Network Lifetime for 20 Targets
Network size: 500m x 500m, sensing range: 75m

19. Network Lifetime for 25 Targets
Network size: 500m x 500m, sensing range: 75m

20. Network Lifetime for Network
Size of 400mx400m
Target: 25, sensing range: 75m

21. Network Lifetime for Network
Size of 500mx500m
Target: 25, sensing range: 75m

22. Network Lifetime for 75m
Sensing Range of Node
Target: 25, Network size: 500m x 500m

23. Network Lifetime for 80m
Sensing Range of Node
Target: 25, Network size: 500m x 500m

24. Network Lifetime for Random
Deployment
Network size: 500m x 500m, sensing range: 75m

25. Deployment using ABC
algorithm
Network size: 500m x 500m, sensing range: 75m

26. Network Lifetime for K-Coverage
(Random Deployment)
Network size: 500m x 500m, sensing range: 75m

27. Network Lifetime for K-Coverage
(Deployment using ABC Algorithm)
Network size: 500m x 500m, sensing range: 75m

28. Experiment Work B
Simulation Cases :
1. Node deployment with same communication
interval
2. Node deployment with distinct random
communication interval
3. Node deployment with distinct communication
interval base on communication cost

29. Simulation Parameters
Parameter Value
Channel Type Wireless 802.15
Propagation Type Two Ray Ground
MAC protocol MAC – 802.15
Queue Type Drop tail
Antenna Omni Antenna
Number of nodes 25
Queue Length 50
Routing protocol AODV
Network area 500 m x 500 m
Packet size 200 bytes
Initial Energy 2 joules
29

30. Case 1 : Node Deployment with
Same Communication Interval

31. Residual Energy of All nodes vs
Time

32. Case 2: Node Deployment with
Distinct Random Communication
Interval
 Energy is inversely proportional to square of
the distance
 Node far from the base station consume more
energy compared to near one
 By allocating different communication interval
to each node helpful to make network energy
consumption rate balance compared to case 1

33. Residual Energy of All nodes vs
Time

34. Case 3: Node Deployment with
Distinct Communication Interval
Based on Communication Cost

35. Case 1 :
Energy Left at Simulation End
Node Energy Node Energy Node Energy
0 1.5216 8 1.5206 16 1.3288
1 1.5066 9 1.5210 17 1.3287
2 1.5212 10 1.5211 18 1.5213
3 1.4236 11 1.4175 19 1.5219
4 1.5216 12 1.4927 20 1.5080
5 1.5077 13 1.5207 21 1.5215
6 1.5215 14 1.4755 22 1.5204
7 1.5218 15 1.5209 23 1.6813
Difference between highest and lowest energy =0.3526 joule

36. Case 2 :
Energy Left at Simulation End
Node Energy Node Energy Node Energy
0 1.6736 8 1.6847 16 1.6849
1 1.6383 9 1.6450 17 1.6714
2 1.6823 10 1.6851 18 1.7172
3 1.6827 11 1.6812 19 1.6004
4 1.6968 12 1.6838 20 1.6808
5 1.6346 13 1.6857 21 1.6819
6 1.6686 14 1.6608 22 1.6600
7 1.6786 15 1.6441 23 1.6813
Difference between highest and lowest energy =0.1168 joule

37. Case 3 :
Energy Left at Simulation End
Node Energy Node Energy Node Energy
0 1.8562 8 1.8585 16 1.8534
1 1.8582 9 1.8563 17 1.8561
2 1.8592 10 1.8588 18 1.8572
3 1.8586 11 1.8576 19 1.8586
4 1.8566 12 1.8592 20 1.8527
5 1.8455 13 1.8589 21 1.8580
6 1.8592 14 1.8424 22 1.8554
7 1.8480 15 1.8597 23 1.8505
Difference between highest and lowest energy =0.0173 joule

38. Conclusion
 Sensing range of node, size of network, number of
target, number of nodes and scheduling have significant
effect on life of network which we have done analyses in
the simulation by increasing no. of target and sensing
area network life decrease but by increasing node’s
sensing radius life increases with effective coverage
level.
 By using artificial bee colony algorithm for node
deployment, we achieve the required target coverage
level and maximize the network lifetime compared to
random deployment. Node deployment by using ABC
algorithm work good for simple as well as k-coverage
application.

39. References
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Scheduling for Target Coverage Problem in Wireless Sensor
Networks”, IEEE sensor journal, vol. 14, no. 3, March 2014.

40. Continue…
7. M. Cardei and J. Wu, “Energy-efficient coverage problems in wireless
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11. Network Simulator -2
http://www.isi.edu/nsnam/ns/doc/index.html

41. Thanking You