An energy-efficient balanced clustering algorithm for wireless sensor networks

Authors:
Zhigao Du;Yi Liu;Depei Qian
Affiliations:
Sino-German Joint Software Institute, School of Computer Science, Beihang University, Beijing, China;Sino-German Joint Software Institute, School of Computer Science, Beihang University, Beijing, China;Sino-German Joint Software Institute, School of Computer Science, Beihang University, Beijing, China
Venue:
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Year:
2009

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Abstract

Clustering is a popular topology control method in wireless sensor networks, which can facilitate the network self-management and make it easy to devise the communication protocols. Also clustering can improve energy efficiency and the network scalability. Existing clustering algorithms concern much about the local energy consumption, but little about the overall energy consumption. A novel energy-efficient, balanced clustering algorithm EEBC is proposed in this paper. In EEBC the sensor nodes are clustered randomly at first, and then they conduct self-adaptive optimization to balance the size of clusters. The structure of the cluster is fixed after the optimization. The operation of EEBC is divided into rounds. At the end of each round the current cluster head selects a node from its cluster members as the next cluster head. The process of the cluster head rotation is transparent to other cluster members. The results of simulations show that EEBC outperforms existing algorithms in energy efficiency and clustering balance.