Genetic Centralized Dynamic Clustering in Wireless Sensor Networks

In order to minimize the energy consumption involved by communications in wireless sensor networks, the use of clustering has proven to be effective. The problem remains to determine the number of cluster-heads, and their distribution in the network to ensure minimal energy consumption and better coverage networks. Unlike Low-Energy Adaptive Clustering Hierarchy algorithm which fixes in advance the number of cluster-heads, and do not guarantee the coverage of the entire network, in this paper, we proposed a genetic centralized dynamic algorithm (GA)-based clustering approach to optimize the clustering configuration (the number of cluster-heads, their distribution and the cluster-members) to limit node energy consumption and the best coverage. The obtained simulation results show that the proposed technique overcomes the Low-Energy Adaptive Clustering Hierarchy algorithm.