Optimal Energy Aware Clustering in Sensor Networks

1. Optimal Energy Aware Clustering in Sensor Networks Soheil Ghiasi*, Ankur Srivastava, Xiaojian Yang, and Majid Sarrafzadeh Computer Science Department, University of California at Los AngelesSENSORS Journal July 2002 Presented by 文政

2. Outline • Introduction • Problem Description • Optimal k-Clustering for Energy Optimization • 2–Clustering to Minimize the Maximum Diameter • Preliminary Experiments • Conclusion

3. Introduction • Low power • Some problem: sensor node clustering, master selection and energy dissipation • k-clustering problem ( k master nodes ) • Balanced ?

4. Problem Description • Effect of clustering quality • Formulate a clustering problem to minimize the communication energy dissipation • There is a maximum number of sensors that each master node can handle

5. Problem Description (cont’d)

6. Problem Description (cont’d) • Given n sensors and k master nodes, we would like to form sets (clusters) such that: • Each point belongs to exactly one of clusters. • Clusters are balanced, i.e

7. Optimal k-Clustering for Energy Optimization

8. Optimal k-Clustering for Energy Optimization (cont’d)

9. 2–Clustering to Minimize the Maximum Diameter • The maximum distance between pairs of points in a cluster is called the diameter • NP-hard • The basis of the approach is a theorem which indicates that for any clustering P with the maximum diameter d, there exists a clustering P' with maximum diameter d', such that P' is linearly separable and d' ≤ d

10. 2–Clustering to Minimize the Maximum Diameter (cont’d)

11. 2–Clustering to Minimize the Maximum Diameter (cont’d)

12. 2–Clustering to Minimize the Maximum Diameter (cont’d)

13. Preliminary Experiments

14. Preliminary Experiments (cont’d)

15. Conclusion • Balanced k-clustering problem can be solved optimally using min-cost network flow