Cluster Formation using Fuzzy Logic in Wireless Sensor Networks

Abstract

The biggest challenges faced by wireless sensor networks (WSNs) are the network lifetime and consumption of energy. To reduce the amount of energy used by WSNs, high quality clustering proves to be a crucial approach. There are multiple criteria that need to be evaluated depending on the cluster's quality and incorporating all these criteria will prove to be cumbersome process, leading to high-quality clustering. Hence, in this paper we propose an algorithm that is used to produce high quality clusters. Cluster quality is set as the deciding criterion to determine the quality of the clusters thereby categorizing them as intra- and inter-clusters based on their distances to eliminate error rate. Using fuzzy logic, the optimal cluster head is chosen. Similarly, based on the maximum and minimum distance between the nodes, the maximum and minimum energy present in every cluster is determined. The major advantages of the proposed methodology are large-scale networks with large nodes count, better scalability, independence of key CHs, low error rate and high reliability. Using internal and external criteria, the validity of the clustering quality can be measured. Experimental simulation shows that the proposed methodology will be useful in improving the network lifetime and energy consumption. Hence the proposed node further enhances the death of the last node and first node when compared using other methodology.