Cat swarm algorithm in wireless sensor networks for optimized cluster head selection: a real time approach

The life time extension in the wireless sensor network (WSN) is the major concern in real time application, if the battery attached with the sensor node life is not optimized properly then the network life fall short. A protocol using a new evolutionary technique, cat swarm optimization (CSO), is designed and implemented in real time to minimize the intra-cluster distances between the cluster members and their cluster heads and optimize the energy distribution for the WSNs. We analyzed the performance of WSN protocol with the help of sensor nodes deployed in a field and grouped in to clusters. The novelty in our proposed scheme is considering the received signal strength, residual battery voltage and intra cluster distance of sensor nodes in cluster head selection with the help of CSO. The result is compared with the well-known protocol Low-energy adaptive clustering hierarchy-centralized (LEACH-C) and the swarm based optimization technique Particle swarm optimization (PSO). It was found that the battery energy level has been increased considerably of the traditional LEACH and PSO algorithm.