Fuzzy Clustering based Cluster Head Selection for IoT enabled WSNs

This work presents a fuzzy mechanism for selecting the optimum cluster head (CH) inside a cluster. During the preliminary simulations, different parameters with different weights are taken into account to make sure that the best CH is chosen, which ameliorates the wireless sensor network (WSN) lifetime. Fuzzy c-means (FCM) clustering is used in the proposed work to select a CH based on the remaining energy ratio, the distance to the sink, the node history, and the node degree. By varying the weights for the above parameters using a brute-force approach, the best-performing weights have been acquired that extend the longevity of a WSN. The simulation results confirm that by incorporating the above-mentioned parameters, network stability is improved by 140.10% and 45.09% as compared to LEACH and FCM, respectively.