A Fuzzy Logic-Based On-Demand Charging Algorithm for Wireless Rechargeable Sensor Networks With Multiple Chargers

Mobile chargers have greatly promoted the wireless rechargeable sensor networks (WRSNs). While most recent works have focused on recharging the WRSNs in an on-demand fashion, little attention has been paid on joint consideration of multiple mobile chargers (MCs) and multi-node energy transfer for determining the charging schedule of energy-hungry nodes. Moreover, most of the schemes leave out the contemplation of multiple network attributes while making scheduling decisions and even they overlook the issue of ill-timed charging response to the nodes with uneven energy consumption rates. In this paper, we address the aforesaid issues together and propose a novel scheduling scheme for on-demand charging in WRSNs. We first present an efficient network partitioning method for distributing the MCs so as to evenly balance their workload. We next adopt the fuzzy logic which blends various network attributes for determining the charging schedule of the MCs. We also formulate an expression to determine the charging threshold for the nodes that vary depending on their energy consumption rate. Extensive simulations are conducted to demonstrate the effectiveness and competitiveness of our scheme. The comparison results reveal that the proposed scheme improves charging performance compared to the state-of-the-art schemes with respect to various performance metrics.