Cluster Head Selection and Cluster Construction using Fuzzy Logic in WSNs

Wireless Sensor Networks (WSNs) consists of a large number of limited memory and battery-powered sensor nodes deployed in the area under observation wirelessly. Therefore, energy efficiency is crucial in WSN. Clustering is a proficient methodology for improving energy efficiency in the network. One of the sensor nodes in every single cluster is considered as a Cluster Head (CH). CH drains its energy faster due to different intra-cluster activities. Therefore, appropriate CH selection is necessary for WSN. In this paper, to select the appropriate CH, fuzzy inference system is applied. The fuzzy input variables are the distance to BS, node degree and remaining energy of sensor node, whereas 'competition radius' and 'size' are two fuzzy output variables. The CHs are selected according to the values of 'competition radius'. The cluster construction is carried out according to the values of 'size'. The sensor nodes get allotted to their respective CH with the nearest distance and the available size of CH. The proposed approach outperforms LEACH and EAUCF algorithm under the evaluation parameters like energy consumption, active sensor nodes per rounds and stability of the network.