An Intelligent Energy Efficient Clustering in Wireless Sensor Networks
One of the main challenges of wireless sensor network is how to improve its life time. The limited energy of nodes is the main obstacle. The authors may overcome this problem by optimizing the nodes' power consumption. A solution is clustering, but optimum clustering of wireless sensor network is a NP-Hard problem. This paper proposes a hybrid algorithm based on Genetic Algorithm and Particle Swarm Optimization to overcome this clustering problem by finding the number of clusters, the cluster heads and the clusters members. Simulation results reveal that this algorithm outperforms LEACH and Genetic Algorithm based clustering scheme.