Genetic Algorithm Based Energy Efficient and Load Balanced Clustering Approach for WSN

Consumption of energy in the wireless sensor networks is major constrain that restrict the impact of the application. It becomes crucial when a more nodes are deployed. Several energy-efficient solutions have been proposed by many researchers. Clustering is one of the most energy-efficient solution that has been proven for the large-size network. However, the performance of the clustering algorithm degrades because of the non-uniform cluster formation and non-uniform cluster heads distribution over the network. To resolve this problem, a Energy Efficient and Load Balanced Clustering Approach for Wireless Sensor Network Using Genetic Algorithm is presented in this paper. The proposed algorithm not only focused on the load balancing and uniform distribution of cluster head but also on the optimal cluster head selection which considers residual energy, inter-cluster, and intra-cluster communication distance. The performance parameters like, lifetime of the network and energy consumption of the proposed algorithm is analyzed with the existent algorithms. The outcomes of the experiment demonstrated that the presented algorithm performs better than the existent algorithms.