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Dynamic clustering using binary multi-objective Particle Swarm Optimization for wireless sensor networks

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4 Author(s)
Abdul Latiff, N.M. ; Sch. of Electr., Newcastle Univ., Newcastle upon Tyne ; Tsimenidis, C.C. ; Sharif, B.S. ; Ladha, C.

In wireless sensor networks, the use of energy efficient infrastructure such as clustering may be used to lengthen the network lifetime and prevent network connectivity degradation. In such systems, the performance of the clustering scheme is generally influenced by the cluster head selection method and the number of clusters. This paper presents a dynamic clustering method with multi-objectives that automatically determines the optimum number of clusters in the network. The algorithm, which is based on binary particle swarm pptimization (PSO), eliminates the need to set the number of clusters a priori. In addition, a multi-objective approach is utilized in the cluster head selection algorithm in order to select the best set of cluster heads. Simulation results demonstrate that the proposed protocol can achieve an optimal number of clusters, as well as prolong the network lifetime and increase the data delivery at the base station when compared to other well known clustering algorithms.

Published in:

Personal, Indoor and Mobile Radio Communications, 2008. PIMRC 2008. IEEE 19th International Symposium on

Date of Conference:

15-18 Sept. 2008