An Efficient Grid-Based Approach for Dynamical Target Coverage in Hybrid Sensor networks

1. An Efficient Grid-Based Approach for Dynamical Target Coverage in Hybrid Sensor networks 混合式感測網路中針對移動目標物的覆蓋率問題提出一個有效率以格網為基礎的方法

2. Outline • Introduction • Related work • Preliminaries • Network model • Proposed approach • Forming the monitoring region • Circle covering to detect coverage hole • Collecting the demand and supply information for healing coverage holes • Minimum cost flow to make the movement plan • Simulation result • Conclusion • Reference

3. Introduction • Structural monitoring • Buildings and Ships • Healthy monitoring • Vehicular applications • Target tracking-based applications • Environment monitoring • Habitat monitoring • Traffic monitoring • Military applications • Wireless sensor networks (WSNs) • Applications

4. Research Issue • Target tracking • Existing researches about target tracking can be divided into two categories: data aggregation (fusion), and location estimation. • the data aggregationinvolves the acquisition, filtering, and correlation of the relevant data from multiple sensor nodes. • The location estimation is to estimate the location of a target in a sensor field based on the received signal intensities at a number of sensor nodes and a priori information about the locations of these sensor nodes.

5. Mobile target Sink Static sensor node

6. Mobile target Sink Mobile sensor node Static sensor node

7. Motivation and Goal • Motive • In order to provide more detail and precise representation about the mobile target. • goal • Proposing a distributed approach to achieving the complete monitoring for a mobile target. • Minimum number of mobile sensor nodes used. • Minimum movement cost.

8. Outline • Introduction • Related work • Preliminaries • Network model • Proposed approach • Forming the monitoring region • Circle covering to detect coverage hole • Collecting the demand and supply information for healing coverage holes • Minimum cost flow to make the movement plan • Simulation result • Conclusion • Reference

9. Related work • G. Wang, G. Cao, P. Berman, and T. La Porta, “Bidding Protocols for Deploying Mobile Sensors,” IEEE Trans. Mobile Computing, Vol. 6, No. 5, pp. 515-528, May 2007. • W.Wang, V. Srinivasan, and K.C.Chua, “Coverage in Hybrid Mobile Sensor Networks,” IEEE Trans. Mobile Computing, vol. 7, no. 11, pp. 1374-1387, Nov. 2008.

10. Outline • Introduction • Related work • Preliminaries • Network model • Proposed approach • Forming the monitoring region • Circle covering to detect coverage hole • Collecting the demand and supply information for healing coverage holes • Minimum cost flow to make the movement plan • Simulation result • Conclusion • Reference

11. Preliminary • Network model • Two-dimensional field divided into a number of grids based on GAF protocol. • Hybrid sensor (static and mobile sensor) • The ratio between these two radiuses is larger than or equal to 2. • Rc: communication range , Rs: sensing range • GPS attached.

12. Preliminary - GAF protocol grid Grid head Sensor node • Our routing problem is based on the GAF protocol, which divides sensor field into multiple grids，and each grid has one head，which can communicate to its neighboring heads directly. The relationship between r and Rc is: Rc r

13. Outline • Introduction • Related work • Preliminaries • Network model • Proposed approach • Forming the monitoring region • Circle covering to detect coverage hole • Collecting the demand and supply information for healing coverage holes • Minimum cost flow to make the movement plan • Simulation result • Conclusion • Reference

14. Working flow Forming the monitoring region (grids) whenever a mobile target appears in the hybrid network Using the circle covering to detect coverage holes Collecting the demand and supply information for healing coverage holes Using the minimum cost flow to make the movement plan

15. Forming the monitoring region Extended monitoring region Original monitoring region

16. Coordinator selection Monitoring region grid head Sensor node coordinator

17. Working flow Forming the monitoring region (grids) whenever a mobile target appears in the hybrid network Using the circle covering to detect coverage holes Collecting the demand and supply information for healing coverage holes Using the minimum cost flow to make the movement plan

18. Circle covering • Minimum Number of Circles to Cover A Rectangle

19. Circle covering Step 1

20. Sensing range union and polygon inclusion Step 3 Step 2

21. Working flow Forming the monitoring region (grids) whenever a mobile target appears in the hybrid network Using the circle covering to detect coverage holes Collecting the demand and supply information for healing coverage holes Using the minimum cost flow to make the movement plan

22. Gathering Information Number of mobile sensors for the coverage support Number of the required mobile sensor nodes 3 2 1 1

23. Finding the search region d d d d d = maximum moving distance 3 1 1 2 3

24. Dispatching mobile nodes 3 2 3 1 2 1 1 1 2 3

25. Working flow Forming the monitoring region (grids) whenever a mobile target appears in the hybrid network Using the circle covering to detect coverage holes Collecting the demand and supply information for healing coverage holes Using the minimum cost flow to make the movement plan

26. Preliminary- Minimum cost flow cost: 12 cost: 10 cost:11 • Minimum cost flow problem: • Given a flow network with costs, find the feasible flow f in G that minimizes cost(f) among all feasible flows f in G. ( 7, 3 ) v1 v2 ( 7, 5 ) ( 7, 4 ) Input flow=5 (6, 3 ) s t ( 3, 1 ) ( 3, 1 ) ( 5, 3 ) ( 5, 5 ) v3 ( 5, 3 ) v4 ( capacity, cost )

27. Minimum cost flow (1)

28. Minimum cost flow (2) Linear equation

29. Minimum cost flow (3)

30. Minimum cost flow (4)

31. Time Complexity (1) Working Stage Time Complexity Forming the monitoring region (grids) whenever a mobile target appears in the hybrid network Using the circle covering to detect coverage holes Collecting the demand and supply information for healing coverage holes Using the minimum cost flow to make the movement plan

32. Time Complexity (2) Communication Complexity Working Stage Forming the monitoring region (grids) whenever a mobile target appears in the hybrid network Using the circle covering to detect coverage holes Collecting the demand and supply information for healing coverage holes Using the minimum cost flow to make the movement plan

33. Outline • Introduction • Related work • Preliminaries • Network model • Proposed approach • Forming the monitoring region • Circle covering to detect coverage hole • Collecting the demand and supply information for healing coverage holes • Minimum cost flow to make the movement plan • Simulation result • Conclusion • Reference

34. Simulation result Simulation setting

35. Simulation result • The following three metrics are concerned: • Average coverage ratio • Average normalized movement cost • Total unified energy consumption Simulation setting (cont.)

36. Simulation result • 3 approaches to be compared: Simulation setting (cont.) • Proposed 1 approach • Ideal approach • Proposed 2 approach

37. Circle covering Centralized circle covering: 72 Distributed circle covering: 81 Proposedapproach1 & 2 Ideal approach

38. Initial target coverage rate Coverage rate of sensor field: 43.789444 % Average target coverage rate : 32.28 %

39. Performance – (1) Average coverage ratio(%)

40. Performance – (3) Average normalized movement cost (m)

41. Performance – (3) Total unified energy consumption

42. Conclusion • This paper has presented a distributedapproach to improving the coverage of a mobile target in the hybrid sensor network. • The proposed approach can assist the execution of the data aggregation and location estimation with more precise computation results. • Simulation results showed that the performance of the proposed approach has small differences with the ideal solution.

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47. Thanks for your attention

48. Wireless sensor network (WSN) Base station (BS) or Sink Sensor Environment Wireless Communication link Sensor node

49. Proposed 1 approach coordinator

50. Ideal approach Super powerful node