Efficient Clustering for Wireless Sensor Networks using Evolutionary Computing

The main objective of this paper is to balance the load among the dissimilar clusters in the network such that lifetime of the network is improved by using Load Balanced Clustering Algorithm (LBCA). In previous algorithm, no relay node is represented to control the network for balancing the load among the clusters. In LBCA, the nodes are grouped into clusters such that network is controlled by the gateway instead of cluster head. This enhances the performance of the network. Load balanced clustering algorithm, improves the communication among dissimilar sensors in the network. To analyze the effectiveness of the technique, the performance of WSNs spread over numerous dissimilar routing procedures are considered. Simulation results indicate that regardless of the routing process used, our method improves the network lifetime. The proposed algorithm improves the performance and success analysis chart and Energy analysis chart, when compared to GA.