EEFMCP: energy efficient fuzzy logic-based multi-clustering protocol

Each round of clustering generally uses a single method to perform the task of clustering. For the enhancement of network capability to better manage the network resources, we extend a new multi-clustering algorithm (EEFMCP) in this paper. We apply a fuzzy inference system to define the various rules in each execution round. Three types of input/ output combinations define the complete working of the clustering protocol. For each node, the different execution round adopts a specific input/output combination to calculate the chance value for cluster head (CH). Multiple input/ output combination of fuzzy variables has better control over the network dynamism. The network feature drastically changes due to the depletion of the energy of sensor nodes. A new closeness index is proposed and utilized for better CH selection. We compare EEFMCP with Low Energy Adaptive Clustering Hierarchy (LEACH), Cluster Head Election mechanism using Fuzzy logic (CHEF), Fuzzy Energy-Aware Unequal Clustering Algorithm (EAUCF), and Fuzzy Logic Based Energy Efficient Clustering Hierarchy (FLECH), the distinct algorithms useful for clustering in WSN. The substantial simulation work shows that the EEFMCP always performs better for different simulation scenarios.