Fault tolerance in wireless sensor networks by Constrained Delaunay Triangulation Coverage Strategy

A Presentation on
Fault Tolerance in Wireless Sensor Networks
by
Constrained Delaunay Triangulation Coverage Strategy

Under Guidance of: Presented by :-
Prof. Dr. Santosh Kumar Swain Ramnesh Dubey
Dept. of Computer science & Engg. Branch: M. Tech.(CSE)
KIIT University Roll no: 1050013

1

Outline
1. Introduction
2. Literature Survey
3. Motivation
4. Problem Definition
5. Objective
6. Proposed Work
7. Simulation Result
8. Comparison
9. Conclusion
10. Future Work
11. References
2

Introduction
Development of sensor nodes,
Advances in with sensing, data processing,
wireless and communicating
Communications components:
low cost
low dimension
low power consumption
Sensing Computing
low memory
Communication low computational power

A wireless sensor network is composed by a large number of sensor
sensing self-powered nodes.
3

Introduction (Contd.)

Energy Efficiency

Deployed Sensor
Coverage
network
Fault tolerant:
The system should be robust against node failure.
4

Literature Survey
• Coverage in WSNs:
Coverage

Fault Deployment Energy Event
Type Radii
Tolerance Strategies Efficiency Transfer

Target Area
Fixed Variable
Coverage coverage

5

Literature Survey (Contd.)

6

Literature Survey (Contd.)
Coverage Strategies
Coverage Strategies

Computational
Force Based Grid Based
Geometry Based

Triangular Lattice Voronoi Diagram

Square Grid Delaunay Triangulation

Hexagonal Grid Constrained Delaunay
Triangulation

7

Motivation
• Coverage strategies proposed so far do not facilitate
fault tolerance and energy efficiency together.
• Sensor networks are energy constrained as they are
battery operated, but in addition to provide fault
tolerant coverage, the energy efficiency of the network
must be maintained.
• K - coverage mechanisms proposed in the literature are
not energy efficient as several sensors report
simultaneously, leading to excessive energy
consumption, congestion, and collisions in the
network.
• This reduces the quality of service and network
performance.
8

Problem Definition

To incorporate in Coverage strategy
• Event Reporting.
• Energy Efficiency.

9

Objective

My objective is to enhances a fault tolerant
coverage protocol that incorporate.

• Event reporting with the help of additional
support structure and

• Energy efficiency by reducing the communication.

10

Proposed Work

Deployment

Coverage

Backup Coverage

Distributed Greedy Algo.

Constrained Delaunay Triangulation
Algo.

And Selection of Backup node

11

Proposed Work (Contd.)

12


13

Distributed Greedy Algo.
• Procedure 2-COVERAGE (S [ ])
• S [ ] is the set of sensor nodes deployed
• R is the region to be covered
• snode ← S[x] : x is randomly selected node
• while (R is not Covered) do
• dbl[i]← snode
• snode← broadcast()
• snode ←recv()
• snode ←maxBenifit()
• i ←i+1
• end while
• end procedure

14

Algorithm for Constrained Delaunay
triangulation CDT
1.Construct DT, set color of each node to WHITE, and
broadcast all its 1-hop neighbor information using the
packet Neighbor_Packet.
2.Nodes having lowest id among its 2-hop neighbors set their
color to BLACK.
3. Each BLACK node chooses a set N of nodes from its 1-hop
neighbors using the following method.
(a) N = empty
(b) n1 = farthest neighbor
(c) N = N ᴜ n1
(d) for i = 2, 3,. . .

15

Algorithm for Constrained Delaunay
triangulation CDT
{
ni = choose ith farthest neighbour
if ni makes more than 60 degree angle with
n1 , n2 , . . . , ni - 1
then N = N ᴜ ni
}
4. Each BLACK node add the constraint edges to the nodes in N and broadcasts these constraint
edges information using the message Constraint _Packet.
5. Each WHITE node sets its color = BROWN if it is other end of any constrained edges received
using Constraint _Packet.
6. Each BROWN node broadcasts its constraint edge information using the control packet
Constraint _Packet.
7. All WHITE and BROWN nodes remove edges connected to it which crosses constraint
edged, this information is broadcasted using Edge cross _Packet.
8. Each-BLACK node places a new edge from the WHITE nodes, from which the edge was
deleted in the previous step to from new triangles. 16

Selection of Backup Nodes Algo.
• Procedure: BK SELECT (dbl [ ])
•
• dbl [ ] is the set of sensor nodes providing 2Coverage
•
• Neighbors [ ] is the set of Triangle Neighbors of each node
•
• i ←0
• while i ≠ dbl.end() do
•
• if dbl[i].area() ≡ Neighbors [ ].area() then
• backup[ j] ← dbl[i]
• PotPri[] ←nearest(Neighbors[],backup[ j])
• PotPri[] ←median(Neighbors[],backup[ j])
• i ← i+1
• end if
• end while
• while i ≠ PotPri.end() do
• if PotPri.area() ≡ Neighbors [ ].area() then
• backup[] ←PotPri[i]
• erase(PotPri[i])
• end if
• end while
• end procedure
17

• Selection of Backup Nodes:

18

• Backup Node Functionality:
Event Detection
Backup Reporting

19

• Event Reporting

a. Several nodes detecting and reporting events to
common forwarder.
b. A node and its forwarder detecting the event.
c. Channel access issues.
20


• Event Reporting
Handle the all three challenges

21

Simulation Result
Simulation Environment
Parameter Low Power Value High Power Value
Number of nodes 50 50
Area Range (m*m) 1000 1000
Transmission range (m) 195 195
Data Packet size 512 512
Bandwidth (Kbps) 2.4 100
Transmit power (mW) 14.88 660
Receive power (mW) 12.50 395
Idle power (mW) 12.36 350
sleep power (mW) 1.4 300

22

Simulation Result (Contd.)
• Throughput Low Power

23

• Throughput High Power

24

• Packet Drop Rate Low Power

25

• Packet Drop Rate High Power

26

• Average Packets End to End Delay Low Power

27

Simulation Result Cont.
• Average Packets End to End Delay High Power

28

Fault Node / Active Node

29

Fault Node / Active Node

30

Energy (Low Power/ High Power)

31

Comparison
Delaunay Triangulation Vs. Constrained
Delaunay Triangulation

32

Comparison (Contd.)
Delaunay Triangulation Vs. Constrained
S.No. Features Delaunay Constrained Delaunay
Triangulation Coverage Triangulation
strategy Coverage strategy

1 Simulation Scenario Matlab Matlab
2 Numbers of 50 50
Nodes
3 Area 1000 1000
4 Dimensions 2D 2D
5 Distance Computed
Formula
6 Sensors Communicate Distance Sensing Distance Sensing
Condition Range Range

33

Comparison Cont.
S.No. Features Delaunay Triangulation Constrained Delaunay
Coverage Triangulation
strategy Coverage strategy
7 Coverage Optimization Coverage Area Coverage

8 Sensing Range Irregular Sensing Range Regular Sensing Range

9 Strategy Geometry Based Geometry Based

34

Comparison (Contd.)
Other Related Work

35

Comparison Cont.

36

Comparison (Contd.)

37

Conclusion
To provide quality service by coverage strategy,
there arises a need for developing protocols to
provide.

• Fault tolerance.
• Event reporting and
• Maintain energy efficiency.

38

Future Work

• Better mechanisms in choosing the minimal
number of nodes for our Coverage Strategy.

• Lowering the contention in the Network.

• Low latency.

39

Dissertation
 R.Dubey, S.K.Swain, C.P.Kashayp, R.Bera “Fault Tolerance in
Wireless Sensor Networks Using Constrained Delaunay
Triangulation”, International Conference on Electrical Engineering
and Computer Science (ICEECS), IRNet, April 2012.
• R.Dubey, S.K.Swain, N.S.Mandal, C.M.Mourya, “Constrained
Delaunay Triangulation for Wireless Sensor Networks", Elsevier Ad
Hoc Networks,2012.( Communicated)

40

References

[1] P.Kumari and Y.Singh. “Delaunay Triangulation Coverage Strategy for Wireless Sensor Networks”. IEEE
(ICCCI), pages 1-5, 2012.
[2] R.H.Abedi, N.Aslam and S.Ghani “Fault Tolerance Analysis of Heterogeneous Wireless Sensor
Network”. CCECE, IEEE International Conference, pages 175-179, 2011.
[3] E.Bulut, Z.Wang and B.K.Szymanski. “The effect of neighbor graph connectivity on coverage
redundancy in Wireless Sensor Network “. IEEE (ICC), pages 1-5, 2010.
[4] M.Marta, Y.Yang and M. Cardei, “Energy-efficient composite event detection in Wireless Sensor
Networks”. In Proceedings of the 4th International Conference on Wireless Algorithms , Systems and
Application , WASA ‘09, Berlin, Heidelberg, Springer-Velag, Pages 94-103, 2009.
[5] C.T.Vu and Y.Li. “Delaunay – Triangulation based complete coverage in Wireless Sensor Networks”.
IEEE (PERCOM), pages 1-5, 2009.
[6] J.Wang, S.Medidi and M.Medidi.”Energy-efficient K-coverage for Wireless Sensor Network with
variable sensing radii”. IEEE (GLOBECOM ), pages 4518-4523, 2009.
[7] D. Satyanarayana and S. V. Rao. “Constrained delaunay triangulation for ad-hoc networks”. J. Comp.
Sys., Netw., and Comm., January, 2008.
[8] D. Wang, B.Xie, and D.P. Agrawal. “Coverage and lifetime optimization of wireless sensor networks
with gaussian distribution”. IEEE Transactions on Mobile Computing, pages 1444-1458, December,
2008.
[9] J. Wang and S. Medidi. “Mesh-based coverage for wireless sensor networks”. IEEE GLOBECOM, pages
1-5, 2008.

41

References Cont.
[10] Jiong Wang and Sirisha Medidi. “Topology control for reliable sensor-to-sink data transport in
sensor networks”. In ICC, pages 3215-3219. IEEE, 2008.
[11] Mohamed Hefeeda. “Randomized k-coverage algorithms for dense sensor networks.” In
Proceedings of INFOCOM Minisymposium, pages 2376-2380, 2007.
[12] Md. M.O.Rashid, M. M. Alam, Md. A. Razzaque, and C. S. Hong. “Reliable event detection and
congestion avoidance in wireless sensor networks.” In Ronald H. Perrott, Barbara M. Chapman,
Jaspal Subhlok, Rodrigo Fernandes de Mello, and Laurence Tianruo Yang, editors, HPCC, volume
4782 of Lecture Notes in Computer Science, pages 521-532. Springer, 2007.
[13] J.Wang and S. Medidi. “Energy ecient coverage with variable sensing radii in wireless sensor
networks.” In Proceedings of the Third IEEE International Conference on Wireless and Mobile
Computing, Networking and Communications, WIMOB '07, pages 61-69, 2007.
[14]C.H.Wu, K.C. Lee, and Y.C.Chung. “A delaunay triangulation based method for wireless sensor
network deployment.” Comput. Commun., 2744-2752,October 2007.
[15] Y. Zhou and M. Medidi. “Energy-ecient contention-resilient medium access for wireless sensor
networks.” IEEE (ICC), pages 3178-3183, 2007.
[16] C. F .Hsin, and M. Liu. “Randomly duty-cycled wireless sensor networks: Dynamics of coverage.”
IEEE Transactions on Wireless Communications, 5,3182-3192, 2006.
[17] K. S.T. Wu and H. C. Jiau. “A two-way coverage mechanism for wireless sensor networks.” In in
Personal, Indoor and Mobile Radio Communications, IEEE 17th International Symposium on, pages
1-5, 2006.

42

References Cont.
[18] S. Megerian, F. Koushanfar, M. Potkonjak, M. B. Srivastava. “Worst and best-case coverage in sensor
networks.” IEEE Transaction on Mobile Computing, pages 84-92, 2005.
[19] G. Xing, X. Wang, Y. Zhang, C. Lu, R. Pless, and C. Gill. “Integrated Coverage and Connectivity
Configuration for in Sensor Networks.” ACM Trans. Sen. Netw., pages36–72, 2005.
[20] O. B. Akan, Akyildiz and F. Ian “Event-to-sink reliable transport in wireless sensor Networks.”
IEEE/ACM Trans. Netw., pages 1003-1016, October 2005.
[21] Mihaela Cardei and D.Z.Du. “Improving wireless sensor network lifetime through power aware
organization.” ACM Wireless Networks, pages 333-340, 2005.
[22] Mihaela Cardei, My T. Thai, Yingshu Li, and Weili Wu. “Energy-ecient target coverage in wireless
sensor networks.” In in IEEE Infocom, pages 1976-1984, 2005.
[23] H.Zhang and J. C.Hou. “Maintaining sensing coverage and connectivity in large sensor networks.”
Ad Hoc & Sensor Wireless Networks, 1, 2005.
[24] C. Wook and S. K. Das. “Trade-of between coverage and data reporting latency for energy
conserving data gathering in wireless sensor networks.” In Mobile Adhoc and Sensor Systems, IEEE
International Conference , pages 503-512, 2004.

43

References Cont.
[25] Z. Zhou, S. Das and H. Gupta. “Connected k-coverage problem in sensor networks”. In Proceedings
of the International Conference on Computer Communications and Networks, pages 373-378,
2004.
[26] Z. Zhou, S. Das and H. Gupta. “Variable radii connected sensor cover in sensor networks”. In Proc.
of the IEEE International Conference on Sensor and Ad Hoc Communications and Networks, 2004.
[27] A. Cerpa and D. Estrin. “Ascent: Adaptive self-conguring sensor networks topologies”. IEEE
Transactions on Mobile Computing, pages 272-285, July 2004.
[28] S. Pattem, S.Poduri and B. Krishnamachari. “Energy-quality tradeos for target tracking in wireless
sensor networks”. In Proceedings of the 2nd international conference on Information processing in
sensor networks, IPSN'03, Berlin, Heidelberg, Springer-Verlag, pages 32-46, 2003.
[29] G. Wang, G. Cao and T. LaPorta. “A bidding protocol for deploying mobile sensors”, 2003.
[30] X.Y.Li, P.J.Wan, and O.Frieder. “Coverage in wireless ad-hoc sensor networks. IEEE Transactions on
Computers . » pages 753-763, 2003.
[31] S. Adlakha and M. Srivastava. “Critical density thresholds for coverage in wireless sensornetworks.”
IEEE Wireless Commun. Networking, pages 16-20, 2003.

44

References Cont.
[32] H. Gupta, S. R. Das and Q. Gu. “Connected sensor cover: self-organization of sensor networks for
efficient query execution”. pages 189-200, 2003.
[33] C. Huang and Y.C. Tseng. “The coverage problem in a wireless sensor network”. In Proceedings of
the 2nd ACM international conference on Wireless Sensor Networks and Applications, WSNA '03,
pages 115-121, 2003.
[34] K. Kar and S. Banerjee. “Node Placement for Connected Coverage in Sensor Networks.” March
2003.
[35] Xiang-Yang Li, Gruia Calinescu, Peng-Jun Wan, and Yu Wang. “Localized delaunay triangulation with
application in ad hoc wireless networks”. IEEE Transaction on Parallel and Distributed System,
14(9):2003, 2003.
[36] B. Liu and D. Towsley. “On the coverage and detectability of wireless sensor networks.” ad hoc
Wireless Networks, 3, 2003.
[37] S. Pattem, S. Poduri and B. Krishnamachari. “Energy-quality tradeos for target tracking in wireless
sensor networks”. In Proceedings of the 2nd international conference on Information processing in
sensor networks, IPSN'03, pages 32-046, Springer-Verlag, 2003.
[38] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. Wireless sensor networks: a survey.
Computer Networks, pages 393-422, 2002.

45

References Cont.
[39] K. Chakrabarty, S. S. Iyengar, H. Qi and E.Cho. “Grid coverage for surveillance and target location in
distributed sensor networks.”IEEE Transactions on Computers, pages 1448-1453, 2002.
[40] A. Howard, M. J. Mataric and G. S. Sukhatme. “Mobile sensor network deployment using potential
fields: A distributed, scalable solution to the area coverage problem”. pages 299-308, 2002.
[41] M.X. Cheng. M. Min X.Jia D. Li D.z Du M. Cardie, D. MacCallum. ‘’Wireless sensor networks with
energy ecient organization.” Jouranal of International Networks, pages 213-229, 2002.
[42] D. Tian and N. D. Georganas. “A Coverage-Preserving Node Scheduling Scheme for LargeWireless
Sensor Networks”. ACM, pages 32–41, 2002.
[43] S. Meguerdichian, F. Koushanfar, M. Potkonjak and M. B. Srivastava. “Coverage problems in wireless
Ad-hoc sensor networks.” In in IEEE INFOCOM, pages 1380-1387, 2001.
[44] S. Meguerdichian, F. Koushanfar, G. Qu and M. Potkonjak.”Exposure in wireless ad-hoc sensor
networks,” 2001.
[45] S. Slijepcevic and M. Potkonjak. “Power ecient organization of wireless sensor networks.” pages
472-476, 2001.
[46] Jie Wu and Hailan Li. “On calculating connected dominating set for efficient routing in ad hoc
wireless networks.” In Proceedings of the 3rd international workshop on Discrete algorithms and
methods for mobile computing and communications, DIALM '99, pages 7-14, ACM,1999.
[47] F. Aurenhammer. “Voronoi diagrams a survey of a fundamental geometric data structure.”ACM
Computing Surveys, pages 345-405, 1991.
[48] Teerawat Issariyakul and Ekram Hossain. “Introduction to Network Simulator NS2.”,Springer
Publishing Company, Incorporated, 1 edition, 2008.

46

References Cont.
[49] S. Lu F. Ye, G. Zhong and L. Zhang. “Energy ecient robust sensing coverage in large sensor
networks”. In Proceedings of the 1st ACM international workshop on Wireless sensor networks and
applications. technical report,UCLA.
[50] M.Cardei and J.Wu, “Coverage in wireless sensor networks.” In M.Ilyas and I.Mahgoub, editors,
Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, pages 361-372. CRC
PRESS LLC.
[51] L. P. Chew ,“Constrained delaunay triangulations.”, 1987.
[52] http://en.wikipedia.org/wiki/MATLAB.
[53] http://www.isi.edu/nsnam/ns/.
[54] Esq David J. Stein,“Wireless Sensor Network Simulator.”, 2006.

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