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Wireless Array Based Sensor Relocation in Mobile Sensor Networks

Wireless Array Based Sensor Relocation in Mobile Sensor Networks. W. Li, Y. I. Kamil and A. Manikas Department of Electrical and Electronic Engineering Imperial College London, UK. ACM IWCMC 2009. Outline. Introduction Problem Goal System model Assume Method Cooperative sensing model

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Wireless Array Based Sensor Relocation in Mobile Sensor Networks

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  1. Wireless Array Based Sensor Relocation in Mobile Sensor Networks W. Li, Y. I. Kamil and A. Manikas Department of Electrical and Electronic Engineering Imperial College London, UK ACM IWCMC 2009

  2. Outline • Introduction • Problem • Goal • System model • Assume • Method • Cooperative sensing model • The local detection diagram(LDD) • Performance evaluations

  3. Introduction • Random deployment is commonly used for some applications in WSNs • However, the actual positions of the sensors cannot be guaranteed or controlled.

  4. Introduction • Many existing approaches tend to exploit mobile sensors to deploy, or relocate to the right positions, in order to obtain the desired coverage.

  5. Introduction • Physics-based • Vector-based algorithm • Geometric-based • Voronoi diagram

  6. Introduction • Vector-based algorithm B A C

  7. Introduction • Voronoi diagram B C A F D E

  8. Problem

  9. System model • [4] W. Li, Y. I. Kamil, and A. Manikas. A wireless array based cooperative sensing model in sensor networks. In IEEE GLOBECOM, pages 1–6, 2008. cooperative sensing beam pattern (CSBP) Any point within a coverage circle, centered at the centroid of the WA, can be covered by the cooperative sensing of the WA through steering the mainlobe towards the signal direction

  10. System model • Wireless array based

  11. Goal • Improve the network sensing coverage

  12. Assume • All nodes have the same transmission range and know their own locations.

  13. Method • Cooperative sensing model • The local detection diagram(LDD)

  14. Local detection diagram(LDD) • The Voronoi diagram can be used to partition the space into polygons(Voronoi cells) B C F A D E

  15. Local detection diagram(LDD) • Finding the local detection edge when the sensing circles of two sensors are B B db pj A A edge of the local detection cell edge of the local detection cell intersecting tangent externally

  16. Local detection diagram(LDD) • Finding the local detection edge when the sensing circles of two sensors are B Dividing line segments between the ith node and its neighboring nodes into two, with their length ratio A edge of the local detection cell intersecting

  17. Local detection diagram(LDD) • Construction of Local Detection Diagram • Step1: A wireless array is regarded as a virtual single “WA-node”, located at the wireless array centroid

  18. Local detection diagram(LDD) • Construction of Local Detection Diagram • Step2:In the network are obtained the edges of the local detection cell of any node

  19. Local detection diagram(LDD) • Construction of Local Detection Diagram • Step3:The smallest polygon encircling any node is considered to be its local detection cell.

  20. Sensor relocation algorithm • However, within the maximum moving distance Lmaxof the RN’s, certain vertex may only be reached by one node. • Lmax: A function of the residual energy. v7 v6 s1 v1 s2 v5 s3 v2 v4 v3

  21. Sensor relocation algorithm • Relocating the Redundant Nodes • Step1: A wireless array first calculates the distance dijbetween any vertex vi that is outside its sensing range and any RN sjinits local detection cell v7 v6 s1 v1 s2 v5 s3 v2 v4 v3

  22. Sensor relocation algorithm • Relocating the Redundant Nodes • Step2:Compare the distance dijwith the Lmax, j of the corresponding RN sj . v7 v6 s1 v1 s2 v5 s3 v2 v4 v3

  23. Sensor relocation algorithm • Relocating the Redundant Nodes • Step3:Vertices are prioritized based on the number of reachable RN’s which satisfiesdij ≤ Lmax, j. v7 v6 s1 v1 s2 v5 s3 v2 v4 v3

  24. Sensor relocation algorithm • Relocating the Redundant Nodes • Step4: According to the vertex order, the RN that is nearest to the ranked vertex will in turn be relocated to the corresponding vertex position. v7 v6 s1 v1 s2 v5 s3 v2 v4 v3

  25. Multiple Healing Detection • Such events are referred to as a multiple healing in the literature v7 s1 v6 v1 s2 s3 v5 v2 v4 v3

  26. Multiple Healing Detection • Self-Detection Scheme • Broadcasts a message containing the coordinates of its target location as well as its distance to this location. v7 s1 v6 v1 s2 s3 v5 v2 v4 v3

  27. Moving Strategy for all other nodes • [7] G. Wang, G. Cao, and T. L. Porta. Movement-assisted sensor deployment. In IEEE INFOCOM, volume 4, pages 2469–2479, 2004. • Since the barycenter(center of mass) location takes into account not only the vertex locations but also the area information about the cell v7 v6 v1 v5 s1 v4 v3

  28. Moving Strategy for all other nodes • However, since the maximum moving distance of each sensor is limited by its Lmax, once this distance is reached, the sensors cannot move any further. v1 v6 v2 v5 s1 v4 v3

  29. Moving Strategy for all other nodes • Movement-Validation Scheme • First determines its actual target location by taking into account Lmax. It then assesses the potential new local coverage Anewat this target location in comparison with the current one Acurrent. v1 v6 v2 v5 s1 v4 v3

  30. Termination • Improvement in coverage is greater than or equal to the threshold value ε.

  31. Performance evaluations

  32. Performance evaluations Coverage percentage against the number of iterations in a (150m × 150m) area with 100 sensors randomly deployed

  33. Performance evaluations Final coverage percentage against the number of deployed sensors in a (150m × 150m) area

  34. Performance evaluations Total moving distance against the number of deployed sensors in a (150m × 150m) area

  35. Performance evaluations The number of moved sensors against the total number of deployed sensors in a (150m×150m) area

  36. Performance evaluations The number of active sensors against the total number of deployed sensors in a (150m×150m) area

  37. Conclusions • The proposed sensor relocation algorithm runs iteratively and in a distributed way. • The main strength of the proposed method lies in the fact that as the sensor density increases, the number of moved sensors as well as active sensors becomes considerably less than the existing sensor relocation algorithm.

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