Implementation of PSO towards Energy Efficient Clustering in Wireless Sensor Networks

Wireless sensor networks are one of the promising and interesting areas of research among researchers because of some of the major reasons like their advancement in real world applications or optimization of resources in sensor nodes. Wireless sensor networks include large number of tiny sensor nodes (depends on the application) which are having the limited resources i.e. energy, communication capabilities etc. Energy conservation in these sensor nodes become very important to enhance the network lifetime. Clustering is one of the energy efficient techniques to achieve this goal. Particle Swarm optimization (PSO) is one of the nature-inspired computation algorithm aims to provide optimal solutions of a given problem. In this paper, progress of different research works conducted to perform energy efficient clustering in WSNs using PSO, has been studied & analyzed. In these research works, various fitness parameters have been considered and evaluated for providing the optimal solutions in terms of cluster head, cluster formation and data routing. This paper aims to focus on study of pure PSO based clustering algorithms and provide their comparative analysis in terms of clustering objectives, type of WSN based on initial energy level of sensor nodes, sink movement, parameters to be integrated in fitness function, performance metrics for evaluation, simulation environment, etc.