Efficient Charging Pad Deployment in Large-Scale WRSNs: A Sink-Outward Strategy

• Published in: Electronics (Basel) Vol. 14; no. 11; p. 2159
• Main Authors: Cheng, Rei-Heng, Yu, Chang-Wu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2025
• Subjects: Aircraft; Algorithms; Connectivity; Data collection; Drone aircraft; Drones; Efficiency; Energy consumption; Greedy algorithms; Nodes; Optimization; Redundancy; Sensors; Traveling salesman problem; Unmanned aerial vehicles; Vehicles; Wireless power transmission; Wireless sensor networks; Wireless telecommunications equipment
• ISSN: 2079-9292; 2079-9292
• DOI: 10.3390/electronics14112159

In recent years, a key problem in wireless sensor networks has been how to effectively deploy the minimum number of wireless charging pads while establishing at least one feasible charging path from the base station. This ensures that the unmanned aerial vehicle can reach and recharge all sensor nodes from the BS. Previous works have often employed greedy algorithms to solve the optimal deployment problem, treating coverage and connectivity as interdependent properties. This has led to excessive constraints on the placement of wireless charging pads, as each newly added charging pad has to satisfy both properties at the same time. Additionally, previous works have overlooked the critical issue of avoiding the occurrence of isolated sensor nodes in uncovered fragmented regions, in deployment. Failing to address this issue requires additional deployment costs to compensate for uncovered nodes. To overcome these limitations, in this work, we propose a sink-outward strategy wireless charging pad deployment algorithm, which deploys charging pads layer by layer from the innermost region outward, prioritizing coverage before connectivity. The proposed sink-outward max covering (SMC) consists of two key steps: initial pad deployment and optimization. The simulation results show that the proposed method SMC combined with the optimization step, called reducing pads by reallocating pads partially (RPRAP), achieves a reduction in pad count of 10.6–19.8% compared with the methods used in previous works, and the execution time demonstrated in previous works is several to tens of times longer than that of SMC combined with RPRAP. Moreover, the proposed redundant pad removal step, RPRAP, not only removes more redundant pads than the methods used in previous works but also drastically reduces processing time in large-scale wireless sensor networks with many redundant pads.