Fuzzy based energy efficient cluster head selection with balanced clusters formation in wireless sensor networks

Abstract

The importance of energy conservation presents a considerable challenge in wireless sensor networks (WSNs), where the sensor nodes (SNs) that constitute the network depend on battery power. Recharging the batteries of SNs in the field is challenging. The clustering technique is a commonly employed method for attaining energy efficiency. In this article, we are proposing a fuzzy-based energy efficient cluster head (CH) selection with the balanced cluster formation (FEECH-BCF) technique. It is a hybrid of the k-means algorithm, low energy adaptive clustering hierarchy- uniform size cluster (LEACH-USC) technique, and fuzzy logic technique. To create the clusters, the k-means approach is employed. The idea of LEACH-USC is used for load balancing to produce clusters with uniform size by assigning member nodes (MNs) from larger clusters to smaller clusters. Optimized CHs are selected using fuzzy based CH selection technique. The k-means algorithm is simple and quick to set up, assigning the membership of SNs to the next best cluster based on centroid locations of clusters reduces intra-cluster distance among clusters, and with the help of fuzzy logic, optimized CHs will be selected. The proposed algorithm performs exceptionally well in attaining uniform energy consumption amongst clusters and extends the network’s lifetime to a greater extent.