An Energy-aware Anchor Point Selection Strategy for Wireless Rechargeable Sensor Networks

Abstract

With the development of wireless power transfer (WPT) technology, it has become a good method to solve energy problem in wireless sensor networks (WSNs). In this paper, a mobile wireless charging vehicle (WCV) is employed in wireless rechargeable sensor networks (WRSNs) to periodically visit every anchor point and charge multiple nodes within its charging radius simultaneously. Traditional anchor point selection strategies for WRSNs almost focus on the location relationship, which take little consideration of energy consumption of sensor nodes. We propose an energy-aware anchor point selection (EAPS) strategy to minimize overall charging time, which consists of stopping time at anchor points and traveling time. We first group nodes into clusters based on the charging radius, and then apply genetic algorithm (GA) to determine the anchor point in every cluster. The simulation results show that EAPS strategy outperforms several state-of-the-art methods in terms of total traveling length and charging time.