Prolonging Network Lifetime and Optimizing Energy Consumption using Particle Swarm Optimization for Mobile Wireless Sensor Networks

There is no doubt, different energy consumption models and techniques are introduced in Mobile Wireless Sensor Networks so far. But still, many researchers are facing challenges to manage energy consumption in MWSN because its growth is expeditiously increasing and that's why there is an immense field for research on this ground. Clustering is one of the significant techniques that can prolong the lifespan of the entire wireless network. In this paper, we propose a novel dynamic hybrid K-means clustering using Particle Swarm Optimization (KC-PSO)to find the best optimal number of clusters and cluster heads for MWSNs. The KC-PSO protocol aiming atto prolong the network lifetime, energy consumption and reduce cluster head overload. The experimental results shows the efficiency of the proposed algorithm in terms of certain crucial parameters such as energy consumption, load balancing, execution time and liveliness of nodes when compared with other existing protocols.