Next century challenges: scalable coordination in sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
TEEN: ARouting Protocol for Enhanced Efficiency in Wireless Sensor Networks
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Distributed optimal dynamic base station positioning in wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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In this project, we developed an adaptive multihop clustering algorithm MaxLife for sensor networks. MaxLife significantly improves sensor network lifetime by balancing energy dissipation and minimizing energy consumption at the same time. The algorithm is compared to Random and MinEnergy algorithms and shows great performance gain. Random is extended from its original design of single hop clustering in [1] to multihop clustering, which elects cluster heads with absolute fairness. However, the idea of rotating the role of cluster heads does not work well in a multihop environment, because relay nodes can also drain out energy quickly. MinEnergy chooses cluster heads to minimize total energy consumption, which leads to large energy disparity and hurts long-term performance. MaxLife on the other hand, uses global optimization techniques and directly maximizes network lifetime. Simulation results verified that MaxLife achieves the best tradeoff between fairness and energy efficiency, and the clustering topology computed from it has significantly longer lifetime than those from the other two algorithms.