Sensor Networks Deployment Using Flip-based Sensors

1. Sensor Networks Deployment Using Flip-based Sensors Sriram Chellappan, Xiaole Bai, Bin Ma and Dong Xuan IEEE International Conference on Mobile Ad hoc and Sensor Systems Conference, 2005. Nov. 7, 2005 Page(s):291 - 298 Presented by Jeffrey

2. Outline • Introduction • Related Work • Mobility Model and Problem Definition • Proposed Solution • Performance Analysis • Conclusions and Future Work

3. Outline • Introduction • Related Work • Mobility Model and Problem Definition • Proposed Solution • Performance Analysis • Conclusions and Future Work

4. Introduction • To improve the sensing coverage if there exist holes • In the literature • If a sensor chooses to move to a desired location, it can do so without any restriction • NOT realistic

5. In Practice • A class of Intelligent Mobile Land Mine Units (IMLM) to be deployed across battlefields have been developed by DARPA • mobility in the units is restricted to only a hoppingmechanism • Each IMLM unit carries onboard fuel tanks and a spark initiation system to propel the hop

6. Outline • Introduction • Related Work • Mobility Model and Problem Definition • Proposed Solution • Performance Analysis • Conclusions and Future Work

7. Related Work • Dynamic Coverage Maintenance Algorithms for Sensor Networks with Limited Mobility • PerCom 2005

8. Minimum Distance Lazy (MDL)

9. Cascaded DCM Scheme

10. Outline • Introduction • Related Work • Mobility Model and Problem Definition • Proposed Solution • Performance Analysis • Conclusions and Future Work

11. Mobility Model and Problem Definition

12. Optimal Movement Plan

13. Outline • Introduction • Related Work • Mobility Model and Problem Definition • Proposed Solution • Performance Analysis • Conclusions and Future Work

14. Proposed Solution • A centralized node (a Base station) collects information about the number of sensors in the regions • Propose a minimum-cost maximum-flow based solution that is executed by the Base-station using the region information • The output of our solution is a movement plan (which sensors should move and where) for the sensors

15. Virtual Graphs

16. :Virtual Graphs-Construction when F=d and R=d

17. Virtual Graphs-Construction when F=d and R>d

18. Proposed Algorithm • We first determine the value of the maximum flow in from all Source vertices to Hole vertices • Using the Edmonds-Karp algorithm

19. To Get The Minimum Cost Flow • Use “Solving minimum-cost flow problems by successive approximation” • It works by starting to find an approximate solution and then iteratively improving the current solution

20. Outline • Introduction • Related Work • Mobility Model and Problem Definition • Proposed Solution • Performance Analysis • Conclusions and Future Work

21. Performance Analysis • Metrics • Coverage Improvement (CI) • CI=Qo-Qi • J • Optimal number of flips as determined by our solution • Flip Demand (FD) • FD=J/CI

22. Evaluation Environment • Field Size • 150  150 • Region Size • 10 •  • change from 0 (uniform distribution) • to 4(highly concentrated at the center of the field)

23. Sensitivity of CI to F when R varies

24. Sensitivity of CI to F when  varies

25. Sensitivity of FD to F

26. Outline • Introduction • Related Work • Mobility Model and Problem Definition • Proposed Solution • Performance Analysis • Conclusions and Future Work

27. Conclusions and Future Work • Proposed a minimum-cost maximum-flow based solution to optimize sensor network deployment using flip-based sensors • Studied the sensitivity of performance to flip distance, under different initial deployment scenarios

28. Future Work • Considered flips in increments of a basic unit (d) • Discrete case • Try to relax this in order to handle continuous mobility, although the overall movement distance (d) is still limited

29. Comments • Strong • Elegantly convert a real world scenario to a math model and solve it • Weak • Is the sensing coverage model realistic?