Abstract

The sustainability and diversity of wireless sensor networks has forwarded the growth of emerging communication models. The survival factors of emerging communication models are energy, computational capacity, and low bandwidth. Energy is a major issue in the survival of wireless sensor networks. The sensor devices occupied the limited battery-operated energy and sank very fast during the propagation of data. The proper utilisation of energy increases the life of the network and enhances the suitability capacity of wireless sensor networks. The issue of energy-based routing protocols is the selection of a cluster head during the transmission of data. The LEACH protocol suffers from the selection process of cluster heads as well. This paper proposed an efficient energy utilisation approach for wireless sensor networks. The proposed algorithm is based on a bio-inspired swarm intelligence algorithm. The two swarm intelligence algorithms, firefly and glow-worm, were integrated and developed into a hybrid swarm intelligence algorithm. The unifying nature of both algorithms reduces the energy utilisation of the selection process of cluster heads. The proposed algorithm simulates and measures standard parameters using MATLAB simulation tools. The proposed algorithm compares with existing algorithms such as LEACH and LEAC-PSO. The experimental results analysis estimated that the proposed algorithm enhances the utilisation of energy by 2-3% instead of existing energy-based algorithms in wireless sensor networks.

Keywords: – WSN, LEACH, PSO, GSO, FA, Cluster, Routing, MATLAB