Fuzzy and PSO Based Clustering Scheme in Underwater Acoustic Sensor Networks Using Energy and Distance Parameters

Abstract

One of the important objectives of underwater acoustic sensor network is to extend the lifespan of a network which depends on the topology control mechanisms. Clustering and routing are important means to extend the network lifetime. This paper proposes a new scheme to form the clusters by using fuzzy clustering and particle swarm optimization (PSO). The scheme works in the following steps. (1) Cluster formation using fuzzy clustering algorithm by considering the parameters like geographic locations and the property of belongingness to the cluster. (2) Finding the number of clusters based on sum of squared error parameter. (3) Fitness function of the cluster is analyzed by considering the parameters like energy consumption, distance between members of the cluster and distance to the Base station. (4) Cluster head nodes are determined by employing PSO-Clustering. The scheme is simulated in MATLAB by comparing with algorithms such as LEACH and KBPSO (K-means and Binary PSO). The experimental results indicate that the proposed scheme performs better in terms of parameters like node death rate, alive nodes, messages received and energy consumption.