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Constructing Load-Balanced Data Aggregation Trees in Probabilistic Wireless Sensor Networks

Constructing Load-Balanced Data Aggregation Trees in Probabilistic Wireless Sensor Networks. Jing (Selena) He, Shouling Ji, Yi Pan, Yingshu Li Department of Computer Science Georgia State University. Outline. Motivation Solution Overview Problem Formulation and Analysis

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Constructing Load-Balanced Data Aggregation Trees in Probabilistic Wireless Sensor Networks

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  1. Constructing Load-Balanced Data Aggregation Trees in Probabilistic Wireless Sensor Networks Jing (Selena) He, Shouling Ji, Yi Pan, Yingshu Li Department of Computer Science Georgia State University

  2. Outline • Motivation • Solution Overview • Problem Formulation and Analysis • Performance Evaulation • Conclusion

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

  4. Motivation Transitional Region Phenomenon

  5. Motivation Probabilistic Network Model

  6. Motivation Load-Balanced Data Aggregation Tree (LBDAT)

  7. Motivation Challenges 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

  8. Outline • Motivation • Solution Overview • Problem Formulation and Analysis • Performance Evaluation • Conclusion

  9. Solution Overview Load-Balanced Maximal Independent Set (LBMIS) Load-Balanced Parent Node Assignment (LBPNA) Load-Balanced Data Aggregation Tree (LBDAT) Connected Maximal Independent Set (CMIS)

  10. Outline • Motivation • Solution Overview • Problem Formulation and Analysis • Performance Evaluation • Conclusion

  11. Load-Balanced Maximal Independent Set (LBMIS) DS Property Constraint IS Property Constraint (quadratic) 1 viis a dominator ωi Relaxing 0otherwise linearization

  12. Approximation Algorithm (Random Rounding) Due to the relaxation enlarged the optimization space, the solution of LP*LBMIScorresponds to a lower bound to the objective of INPLBMIS .

  13. Load-Balanced Maximal Independent Set (LBMIS)

  14. Connected Maximal Independent Set (CMIS)

  15. Load-Balanced Parent Node Assignment (LBPNA) Each dominatee can be allocated to only one dominator Relaxing

  16. Load-Balanced Parent Node Assignment (LBPNA)

  17. Outline • Motivation • Solution Overview • Problem Formulation and Analysis • Performance Evaluation • Conclusion

  18. Performance Evaluation Our method Other’s Method • LBDAT prolong network lifetime by 42% on average compared with DAT

  19. Outline • Motivation • Solution Overview • Problem Formulation and Analysis • Performance Evaluation • Conclusion

  20. Conclusions • LBDAT is NP-Complete, constructed 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.

  21. Q & A

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