Bounded relay hop mobile data gathering in wireless sensor networks

1. Bounded relay hop mobile data gathering in wireless sensor networks Miao Zhao and Yuanyuan Yang Department of Electrical and Computer Engineering State University of New York IEEE MASS 2009

2. Outline • Introduction • Goal • BRH-MDC Problem • Centralized Algorithm for BRH-MDC Problem • Distributed Algorithm for BRH-MDC Problem • Performance Evaluation • Conclusion

3. Introduction • Data gathering in WSN • Multi-hop relay • High energy consumption

4. Energy saving tradeoff Collection latency Introduction • Employing mobile collectors • Low energy consumption • High collection latency

5. Goal • Proposing a polling-based approach that pursues a tradeoff between the energy saving and data collection latency • Achieves a balance between the relay hop count for local data aggregation and the moving tour length of the mobile collector.

6. BRH-MDC Problem • Network assumption • The mobile collector has the freedom to move to any place in the sensing field

7. Polling point Sensor Static data sink d-hop bound Relay routing path Mobile collector tour BRH-MDC Problem • Basic idea • Find a set of special nodes referred to as polling points (PPs) in the network • The PPs are compactly distributed and close to the data sink. • The number of the PPs is the smallest

8. 4 energy_unit/packet 3 energy_unit/packet 2-hop bound 3 energy_unit/packet BRH-MDC Problem • Relay hop count should be bounded ( d-hop ) • A sensor network may expect to achieve a certain level of systematic energy efficiency. Eg. If each transmission costs one unit of energy and the energy efficiency of 0.33 packet/energy_unit is expected • The bound is necessary due to buffer constraint on the sensors.

9. Centralized Algorithm for BRH-MDC Problem • Shortest Path Tree based Data Collection Algorithm (SPT-DCA) • Energy saving and data collection latency • Constraint of the relay hop bound (d-hop) • The sensors selected as the PPs are compactly distributed and close to the data sink. • The number of the PPs is the smallest under the constraint of the relay hop bound.

10. Centralized Algorithm for BRH-MDC Problem • Shortest Path Tree based Data Collection Algorithm (SPT-DCA) • Energy saving and data collection latency • Constraint of the relay hop bound (d-hop) • The sensors selected as the PPs are compactly distributed and close to the data sink. • The number of the PPs is the smallest under the constraint of the relay hop bound. 6 20 5 Iteration 1 14 16 24 15 2 17 21 d-hop = 2-hop 7 8 1 25 19 11 18 3 13 10 23 12 22 9 4

11. = 1-hop Centralized Algorithm for BRH-MDC Problem • Shortest Path Tree based Data Collection Algorithm (SPT-DCA) • Energy saving and data collection latency • Constraint of the relay hop bound (d-hop) • The sensors selected as the PPs are compactly distributed and close to the data sink. • The number of the PPs is the smallest under the constraint of the relay hop bound. 6 20 5 Iteration 2 14 16 24 15 2 17 21 d-hop = 2-hop 7 8 1 25 19 11 18 3 13 10 23 12 22 9 4

12. Centralized Algorithm for BRH-MDC Problem • Shortest Path Tree based Data Collection Algorithm (SPT-DCA) • Energy saving and data collection latency • Constraint of the relay hop bound (d-hop) • The sensors selected as the PPs are compactly distributed and close to the data sink. • The number of the PPs is the smallest under the constraint of the relay hop bound. 6 20 5 Final result 14 16 24 15 2 17 21 d-hop = 2-hop 7 8 1 25 19 11 18 3 13 10 23 12 22 9 4

13. Distributed Algorithm for BRH-MDC Problem • Priority based PP selection algorithm (PB-PSA) • Energy saving and data collection latency • The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range. • The secondary parameter is the minimum hop count to the data sink. TENTA_ PP

14. TENTA_ PP =3 TENTA_ PP =3 TENTA_ PP =3 TENTA_ PP =3 • Priority based PP selection algorithm (PB-PSA) • Energy saving and data collection latency • The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range. • The secondary parameter is the minimum hop count to the data sink. Round 1 d-hop=2-hop 1 2 3 6 TENTA_ PP =4 TENTA_ PP 4 5 TENTA_ PP = 5 TENTA_ PP = 5,4,6 TENTA_ PP =4

15. TENTA_ PP =3 TENTA_ PP =3 TENTA_ PP =3 TENTA_ PP =3 • Priority based PP selection algorithm (PB-PSA) • Energy saving and data collection latency • The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range. • The secondary parameter is the minimum hop count to the data sink. Round 2 d-hop=2-hop 1 2 3 6 TENTA_ PP =3 TENTA_ PP =4 TENTA_ PP 4 5 TENTA_ PP =4,3 TENTA_ PP =3 TENTA_ PP =4

16. Round = 1 TENTA_ PP =2 TENTA_ PP =3 TENTA_ PP =4 TENTA_ PP =5 TENTA_ PP =5 Round =2 TENTA_ PP =3 TENTA_ PP =4 TENTA_ PP =5 TENTA_ PP =5 TENTA_ PP =5 • The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range. • Priority based PP selection algorithm (PB-PSA) • Energy saving and data collection latency • The secondary parameter is the minimum hop count to the data sink. d-hop=2-hop 2 4 1 3 5 TENTA_ PP =1 TENTA_ PP =2 TENTA_ PP =3 TENTA_ PP =4 TENTA_ PP =5

17. TENTA_ PP =3 TENTA_ PP =3 • Priority based PP selection algorithm (PB-PSA) • Energy saving and data collection latency • The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range. • The secondary parameter is the minimum hop count to the data sink. 1 2 3 6 TENTA_ PP =3 Declar 4 5 TENTA_ PP =3 TENTA_ PP =3

18. PP =3 PP =3 PP =3 PP =3 PP =3 • Priority based PP selection algorithm (PB-PSA) • Energy saving and data collection latency • The primary parameter is the number of d-hop neighbors, which are the sensors in its d-hop range. • The secondary parameter is the minimum hop count to the data sink. 1 2 3 6 Declar 4 5 Declar

19. Performance Evaluation • Simulation Parameter • A network with 30 sensors scattered over a 70m x 70m square area. • d is set to 2.(2-hop bound)

20. Performance Evaluation • Comparison with the Optimal Solution

21. Performance Evaluation • Performance of SPT-DCA and PB-PSA • Increasing relay hop bound d

22. Performance Evaluation • Performance of SPT-DCA and PB-PSA • Increasing transmission range Rs

23. "Data gathering in wireless sensor networks with mobile collectors," IEEE IPDPS, 2008. "Multiple controlled mobile elements (data mules) for data collection in sensor networks,“ IEEE DCOSS 2005. Performance Evaluation • Comparison with SHDG and CME

24. Performance Evaluation • Comparison with SHDG and CME • Increasing the number of sensors

25. Performance Evaluation • Comparison with SHDG and CME • Increasing the side length of the area (L)

26. Conclusion • The paper have studied mobile data gathering in wireless sensor networks by exploring the tradeoff between the relay hop count of sensors for local data aggregation and the tour length of the mobile collector. • Then presented two efficient algorithms to give practically good solutions. • The results demonstrate that the proposed algorithms can greatly shorten the data collection tour length with a small relay hop bound

27. Thank you very much~