Selection of Metaheuristic Algorithm to Design Wireless Sensor Network

Abstract

The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance. The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’ access network. The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness. Coverage and energy usage are mostly determined by successful sensor placement strategies. Nature-inspired algorithms are the most effective solution for short sensor lifetime. The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks (WSNs’) maximum network coverage. Moreover, it identifies quantity of installed sensor nodes for the given area. Superiority of algorithm has been identified based on value of optimized energy. The first half of the paper’s literature on nature-inspired algorithms is discussed. Later six metaheuristics algorithms (Grey wolf, Ant lion, Dragonfly, Whale, Moth flame, Sine cosine optimizer) are compared for optimal coverage of WSNs. The simulation outcomes confirm that whale optimization algorithm (WOA) gives optimized Energy with improved network coverage with the least number of nodes. This comparison will be helpful for researchers who will use WSNs in their applications.