1. Covering Points of Interest with Mobile Sensors Milan Erdelj, Tahiry Razafindralambo and David Simplot-Ryl INRIA Lille - Nord Europe IEEE Transactions on Parallel and Distributed Systems (TPDS) Digital Object Identifier (DOI): 10.1109/TPDS.2012.46

2. Outline Introduction Problem & Goals Assumptions and Network Model PoI Deployment Algorithm (PDA) –Simulations for Static PoI Strategies and simulations for Moving PoI Strategies and simulations for Multiple PoIs Conclusion

3. Introduction Recently, wireless sensor networks have received a lot of attention due to their potential applications in various areas –such as environmental monitoring. The placement of sensors related to coverage issues is intensively studied in the literature, and can be divided into three categories. –Full coverage –Barrier coverage –Target coverage

4. Introduction The full coverage problem (Areas of Interest, AoI) –aims at covering the whole area. –Sensors are deployed to maximize the covered area.

5. The barrier coverage problem (Lines of Interest, LoI) –aims at detecting intrusion on a given area. –Sensors have to form a dense barrier in order to detect each event that crosses the barrier. Introduction USA Intruder

6. Introduction The target coverage problem (Points of Interest, PoI) –aims at monitoring specific points in the field of interest. MuseumCampusMilitary

7. Introduction The target coverage problem (Points of Interest, PoI) –aims at monitoring specific points in the field of interest. Indeed, sensors have to be correctly placed –to monitor the events –connection between the monitoring sensors and a base station have to be kept to report data.

8. Problem However, existing sensor deployment algorithms belong to the offline schemes –To provide optimal placement of sensors –For static sensors and PoIs

9. Goals Design the online and distributed sensor deployment schemes for sensors with motion capabilities –To cover PoIs (1) Static PoI, (2) Moving PoI, (3) Multiple PoIs –To maintain the connectivity between each sensor and base station all along the deployment procedure base station Point of interest

10. Goals Design the online and distributed sensor deployment schemes for sensors with motion capabilities –To cover PoIs (1) Static PoI, (2) Moving PoI, (3) Multiple PoIs –To maintain the connectivity between each sensor and base station all along the deployment procedure

11. Assumptions and Network Model This paper considers a network composed by mobile sensors and a fixed base station. –At the beginning of the deployment, the base station already possesses all the information about PoI locations. Tasks of the base station –Spread out the information about PoI locations among the sensors –Collect the information reported from the sensors about the events happening at the PoI

12. Assumptions and Network Model At the beginning of the deployment, the sensors are connected to the base station. –Communication range: R Sensors are randomly spread out around the base station at a maximum distance of d < R/4 –Each sensor has the location knowledge of its 2-hop neighborhood.

13. Assumptions and Network Model Let G(V,E) be the graph representing the sensor network. V is the set of vertices each one representing a sensor. E  V 2 is the set of edges G(V,E)G(V,E)

14. Assumptions and Network Model E = {(u,v)  V 2 | u  v  d(u,v) ≤ R}, –where d(u,v) is the Euclidean distance between sensors u and v N(u) = {v  V | d(u,v) ≤ R} is the set of 1-hop neighbors of sensor u. G(V,E)G(V,E)

15. Assumptions and Network Model Depending on the chosen subset of neighbors –keeping these local connections can provide a global connectivity of the network. –Relative Neighborhood Graphs (RNG) RNG(G) G(V,E)G(V,E)

16. Let RNG(G) be the Relative Neighborhood Graph extracted from G(V,E). RNG(G) = (V,E rng ), where E rng = {(u,v)  E | w  (N(u) ∩N(v))  d(u,w) < d(u,v)  d(v,w) < d(u,v)}. Assumptions and Network Model vu w 

17. N RNG (u) is the set of u's RNG neighbors. N RNG (u) = {v,w  N(u)  v  N(w) | d(u,v) < d(v,w)  d(u,w) < d(v,w)}. RNG + (u) is the farthest sensor of N RNG (u) d + (u) is distance between u and RNG + (u) wv u

18. RNG –keeps sensor connectivity with short-distance neighbors –minimizes the number of connectivity sensors –improves the coverage quality Assumptions and Network Model pb uv R R/4 b: base station

19. PoI Deployment Algorithm (PDA)

20. The direction of a sensor is given by the unit vector

21. PoI Deployment Algorithm (PDA) RNG + (u) is the farthest sensor of N RNG (u) d + (u) is distance between u and RNG + (u) The maximum distance –which the sensor can travel while maintaining connectivity with its RNG neighbors

22. PoI Deployment Algorithm (PDA) The maximum distance d –if d <  1 or d <  2, then d = 0  1 is used to avoid an infinite sequence of sensor movements  2 is used to stop sensor movement when their distance to the PoI is below this threshold

25. Simulations for Static PoI Simulation parameters –PoI is located at position p(70,100) –Number of sensors: 20

26. Simulations for Static PoI Coverage quality –Number of covering sensors –Distance between the base station and PoI

27. Simulations for Static PoI Deployment speed (BS to PoI distance: 100, 20 sensors) –Number of covering sensors –Time Mean speed: 0.75m/s, 90m covered distance after 120s Max speed: 1m/s, communication range(10)/ decision period(5)=2m/s 2/2=1m/s

28. Strategies for Moving PoI PoI is first located at p’(70,0) and then at p’’(70,70) after 200s.

29. Strategies for Moving PoI PoI is first located at p’(70,0) and then at p’’(70,70) after 200s.

30. Strategies for Moving PoI PoI is first located at p’(70,0) and then at p’’(70,70) after 200s.

31. Simulations for Moving PoI Coverage quality

32. Simulations for Moving PoI Deployment speed

33. Strategies for Multiple PoIs 30 sensors PoI 1 (90,50) PoI 2 (50,90)

34. Strategies for Multiple PoIs 30 sensors PoI 1 (90,50) PoI 2 (50,90)

35. Simulations for Multiple PoIs Coverage quality and deployment speed

36. Implementation Wifibot Robots –Wifibot. Mobile robots, www.wifibot.com. –equipped with VGA video camera user control software WiFi device for communicating two IR proximity sensors on the front side of the chassis

37. Implementation I-PDA for implementation

38. Implementation I-PDA for implementation –In case of obstacle detection –obstacle avoidance steps are run iteratively until all the auxiliary PoIs are covered or the boundary of the communication range is reached

39. Implementation

42. Conclusion This paper proposes PDA algorithm to achieve PoI coverage. –static, moving and multiple PoI coverage are provided Connectivity between each sensor and the base station is kept all along the deployment procedure. The proposed algorithm is local i.e., every decision taken is based on local neighborhood information only and does not require synchronization. TheEND