1. Collaborative Broadcasting and Compression in Cluster-based Wireless Sensor Networks Anh Tuan Hoang and Mehul Motani National University of Singapore Wireless Sensor Networks, 2005

2. Outline  Introduction  Network architecture  Collaborative Broadcasting and Compression (CBC)  Simulation  Conclusions

3. Introduction  Conserve energy and increase lifetime  This paper deals with removing redundancy due to spatial correlation when nodes are carrying out joint data compression.

4. Introduction A D C B Point to Point link Model Omni-directional antennas

5. Network Architecture Commend Center 1.Make control and management more scalable 2.Data compression and aggregation 3.Forward hops is reduced

6. Sensing & Communication  Time is divided into intervals of equal duration called data-gathering round.  Within each cluster sensor using TDMA to send data to the cluster head directly.  Inter-cluster interference is negligible t Data gathering round

7. Energy model  The energy consumed to receive r bits is  E rx (r) = E e * r  The energy consumed to transmit r bits  E tx (r,d) = E e * r + E a * d α * r  The energy consumed to compress r bits is  E cp *(r) = E c * r

8. Collaborative Broadcasting and Compression : a simple case C is the cluster head E B = E e * r B + E a * d 2 BC * r B E B|A = E e * r A + E c * r A + E e * r B|A + E a * d 2 BC * r B|A

9. Collaborative Broadcasting and Compression : a simple case  Let r A = r B = R while r B|A = r, r <= R  d BC is large, i.e., node B locates far from the cluster head C  r/R is small, i.e., a significant reduction in the size of the data of B can be achieved by compressing base on A Compression ratio

10. Collaborative Broadcasting and Compression : a simple case  Policy μ 1 : Let A transmit to C first  E μ1 A = E A = E e * r A + E a * d 2 AC * r A  E μ1 B = min { E B, }  Policy μ 2 : Let B transmit to C first  arg max {t 1 + t 2 }  E μ1 A * t 1 + E μ2 A * t 2 <= e A (initial energy of A)  E μ1 B * t 1 + E μ2 B * t 2 <= e B

11. Collaborative Broadcasting and Compression : general network  Transmission order should be determined  Each node need to know which other node it should compress on  Let be a subset of the set of all K sensors, a CBC policy μ v specify for each node  μ v (k) = 0 if k is not allowed to compress based on another node  μ v (k) = i, if k is allowed to compress based on i.

12. Collaborative Broadcasting and Compression : general network  A CBC scheme is a policy-time set  CBC policy μ v i is employed for t v i data gathering rounds  Each node in v does not consume more than its residual energy

13. Collaborative Broadcasting and Compression : general network 3 7-3+1alive sensors The objective of the optimization problem in phase k is to find a CBC scheme that maximize the time when one of the K-k+1 alive sensors

14. Collaborative Broadcasting and Compression : general network

15. Simulation 100 * 100 m

16. Simulation

17. Simulation

18. Simulation

19. Conclusions  Propose an approach in which the inherent broadcast nature f the wireless medium is used by sensor nodes to carry out joint data compression and conserve energy.  Propose a heuristic algorithm which has significantly lower computational complexity.  Extending our approach to non-cluster based networks and designing scalable efficient heuristic algorithm.