Energy efficient zone‐based clustering algorithm using fuzzy inference system for wireless sensor networks

In Wireless Sensor Networks (WSN), as sensor nodes have limited energy, the design of an energy‐efficient clustering technique is a critical challenge to be addressed. We propose an Energy‐Efficient Zone‐based Clustering algorithm for WSN that works efficiently in large area WSN as well. In the proposed method, the sensing field is divided into equal size zones, and one Zone Monitor is selected in each zone. The distance of a Zone Monitor from the Base Station is considered in the calculation of the number of desired Cluster Heads (CHs) in its zone for implementing Unequal clustering. The CHs are selected such that they are uniformly distributed inside each zone to conserve the energy of sensor nodes needed for intra‐cluster transmission. Also, for better load balancing among the selected CHs, we propose that cluster size should be uniform at zone level. Hence, after the CHs are selected, the remaining sensor nodes in a zone decide to become a cluster member of one of the selected CHs using a fuzzy‐based cluster formation technique. We compare the proposed algorithm with other approaches for three different network scenarios using parameters such as the number of alive nodes, the first node dies, half of the nodes die, the last node dies, the amount of data received at Base Station, and total remaining energy. Simulation results show that the proposed clustering algorithm provides better performance than other methods.