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Energy-Efficient Target Coverage in Wireless Sensor Networks

Energy-Efficient Target Coverage in Wireless Sensor Networks. PLLAB 김성민. Outline. Introduction Proposal Maximum Set Covers(MSC) Problem MSC Problem is NP-Complete MSC heuristic Conclusion. Introduction. Characteristics of WSN Dense Limited resourse ….

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Energy-Efficient Target Coverage in Wireless Sensor Networks

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  1. Energy-Efficient Target Coverage in Wireless Sensor Networks PLLAB 김성민

  2. Outline • Introduction • Proposal • Maximum Set Covers(MSC) Problem • MSC Problem is NP-Complete • MSC heuristic • Conclusion

  3. Introduction • Characteristics of WSN • Dense • Limited resourse • … Critical Issue: Power Scarcity!!!

  4. Target Coverage Problem • Given • m targets • n sensors randomly deployed • Assume • same remaining energy • same range • How to optimize the sensor energy utilization?

  5. Proposal C = {s1, s2, s3, s4} R = {r1, r2, r3} Disjoint sets: S1 = {s1, s2} S2 = {s3, s4} Lifetime G = 2 Our Approach: S1 = {s1, s2} with t1 = .5; S2 = {s2, s3} with t2 = .5 S3 = {s1, s3} with t3 = .5; S4 = {s4} with t4 = 1 Lifetime G = 2.5

  6. Proposal

  7. Maximum Set Covers (MSC) • Given C : set of sensors R : set of targets • Goal • Determine a number of set covers S1, …, Sp and t1,…,tp • Where: • Si completely covers R • Maximize t1 + … + tp

  8. Maximum Set Covers (MSC) • Theorem: MSC is NP-Complete • MSC problem belongs to the class NP and is NP-hard, so MSC is NP-Complete • Proof ???? • So, this paper presents Two heuristics.

  9. MSC Heuristic • We first model the MSC problem as an Integer Programming • Given : • A set of n sensor nodes: C = {s1 , s2, …, sn} • A set of m targets: R={r1 , r2, …, rm} • The relationship between sensors and targets: • Ck = { i | sensor si covers target rk} s1 r1 C = {s1, s2, s3}; s2 r2 R = {r1, r2, r3} s3 r3 C1 = {1,3}; C2 = {1,2}; C3 = {2,3} • Variables: • xij = 1 if si ∈ Sj, otherwise xij = 0 • tj ∈ [0, 1], represents the time allocated for Sj

  10. MSC Heuristic (IP) • first constraint : each sensor life time <=1 • second constraint : each target is covered by at least one sensor

  11. MSC Heuristic (IP) • The term xijtj is not linear • Therefore we set yij = xijtj

  12. MSC Heuristic (LP) • We are ready to introduce LP-MSC heuristic

  13. MSC Heuristic (LP) O (p3n3)

  14. Greedy Heuristic • Input parameter • C - the set of sensors • R - the set of targets • w – sensor lifetime granularity, 0 < w <= 1

  15. Greedy Heuristic O (im2n)

  16. Result

  17. Result

  18. Result

  19. Conclusion • Schedule the sensor node activity to alternate between sleep and active mode • Our contributions: • Propose maximum covers set approach • Prove it is NP-complete • Propose an efficient heuristic

  20. 감사합니다

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