Genetic Algorithm Based Clustering for Large-Scale Sensor Networks

Despite the success of various clustering algorithms for Wireless Sensor Networks (WSNs), there are few works that consider the interference between clusters. Obviously, interference-free clustering makes the communication more efficient and achieves energy saving. In this paper we propose a new clustering method for large-scale sensor networks. With this method the network is partitioned into clusters. Intra-cluster communication in a cluster has no interference by its neighbor clusters. Moreover, the proposed clustering is based on a Genetic Algorithm (GA), which can achieve optimal performance in terms of the number of isolated nodes. This is demonstrated by the simulation analysis.

Abstract licence: CC BY-NC-ND

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