1. C ONSTRUCTING L OAD -B ALANCED D ATA A GGREGATION T REES IN P ROBABILISTIC W IRELESS S ENSOR N ETWORKS Jing (Selena) He, Shouling Ji, Yi Pan, Yingshu Li Department of Computer Science Georgia State University

2. O UTLINE Motivation Solution Overview Problem Formulation and Analysis Performance Evaulation Conclusion 2

3. 3 Motivation Probabilistic Network Model Load Balanced Data Aggregation Tree Challenges

4. T RANSITIONAL R EGION P HENOMENON Motivation 4 Link Length0 – 2.6 M2.6 – 6 M> 6 M λ > 80%780 Total82715

5. P ROBABILISTIC N ETWORK M ODEL 5 Motivation

6. L OAD -B ALANCED D ATA A GGREGATION T REE (LBDAT) 6 Motivation

7. C HALLENGES How to measure the traffic load of each node under Probabilistic Network Model (PNM)? Potential load Actual load How to find a Load-Balanced Data Aggregation Tree (LBDAT)? NP-Complete 7 Motivation

8. O UTLINE Motivation Solution Overview Problem Formulation and Analysis Performance Evaluation Conclusion 8

9. S OLUTION O VERVIEW 9 9 Load-Balanced Maximal Independent Set (LBMIS) Connected Maximal Independent Set (CMIS)Load-Balanced Parent Node Assignment (LBPNA)Load-Balanced Data Aggregation Tree (LBDAT)

10. O UTLINE Motivation Solution Overview Problem Formulation and Analysis Performance Evaluation Conclusion 10

11. L OAD -B ALANCED M AXIMAL I NDEPENDENT S ET (LBMIS) 11 DS Property Constraint IS Property Constraint linearization Relaxing (quadratic) ωiωi 1 v i is a dominator 0 otherwise

12. A PPROXIMATION A LGORITHM (R ANDOM R OUNDING ) 12 Due to the relaxation enlarged the optimization space, the solution of LP * LBMIS corresponds to a lower bound to the objective of INP LBMIS.

13. L OAD -B ALANCED M AXIMAL I NDEPENDENT S ET (LBMIS) 13

14. C ONNECTED M AXIMAL I NDEPENDENT S ET (CMIS) 14

15. Relaxing L OAD -B ALANCED P ARENT N ODE A SSIGNMENT (LBPNA) 15 Each dominatee can be allocated to only one dominator

16. 16 L OAD -B ALANCED P ARENT N ODE A SSIGNMENT (LBPNA)

17. O UTLINE Motivation Solution Overview Problem Formulation and Analysis Performance Evaluation Conclusion 17

18. P ERFORMANCE E VALUATION 18 Our method Other’s Method LBDAT prolong network lifetime by 42% on average compared with DAT

19. O UTLINE Motivation Solution Overview Problem Formulation and Analysis Performance Evaluation Conclusion 19

20. C ONCLUSIONS LBDAT is NP-Complete, c onstructed in three steps: Load-Balanced Maximal Independent Set (MDMIS) Connected Maximal Independent Set (CMIS) Load-Balanced Parent Node Allocation (LBPNA) Approximation algorithms and performance ratio analysis are presented. 20

21. 21 Q & A