Fuzzy based enhanced cluster head selection (FBECS) for WSN

For efficient data gathering in context to energy dissipation, WSN is divided into clusters. Clustering not only organizes a deployed network into connected hierarchy but also balances the network load thereby dragging out the lifetime of the system. In cluster based WSN, every sensor node sends the gathered information to the coordinator of their respective cluster. The cluster coordinator holds the responsibility of aggregation of the collected information & route it to the sink of the deployed network. In this paper, a fuzzy based balanced cost CH selection algorithm (FBECS) is proposed which contemplates the remnant energy, farness from sink and the density of the node in its vicinity as input to Fuzzy Inference System. Eligibility index is calculated for each node for the selection of CH role. This protocol ensures load balancing by choosing the best candidate for the role of the coordinator of the cluster by considering the probability assigned to each sensor node. The experimental results validates the performance of FBECS to its counterparts BCSA and LEACH on the basis of better stability period, prolong lifetime with load balancing and large information forwarding to sink. (C) 2018 The Authors. Production and hosting by Elsevier B.V.