An Onion-Peeling Like Wireless Charging Pad Deployment Algorithm

In recent years, unmanned aerial vehicles (UAVs) equipped with wireless chargers have been utilized as mobile charging units to flexibly recharge energy-depleted sensor nodes in wireless sensor networks. However, the endurance of UAVs remains a critical challenge. By deploying wireless charging pads to provide energy replenishment, UAVs can sustain their operations and successfully complete their charging tasks. Therefore, a key problem is how to effectively deploy the minimum number of wireless charging pads while establishing at least one feasible charging path from the base station (BS). This ensures that the UAV can reach and recharge all sensor nodes from BS. When designing an optimization algorithm for wireless charging pad deployment, connectivity, coverage, and geometric properties must be considered simultaneously. However, previous approaches often employed greedy algorithms to solve the optimal deployment problem, treating coverage and connectivity as interdependent properties. This led to excessive constraints on the placement of wireless charging pads, as each newly added charging pad had to satisfy both properties at the same time. Additionally, previous works overlooked a critical issue, which is avoiding the occurrence of isolated sensor nodes in uncovered fragmented regions, in deployment. Failing to address this issue would require additional deployment costs to compensate for uncovered nodes. This study focuses on addressing these challenges by proposing a novel deployment strategy to enhance the energy replenishment efficiency and overall performance of wireless charging sensor networks. To overcome the limitations of previous methods, we apply computational geometry techniques to develop a more effective deployment algorithm. Our proposed onion-peeling like wireless charging pad deployment algorithm deploys charging pads layer by layer from the outermost region inward, prioritizing coverage before connectivity. Simulation results demonstrate that the proposed approach significantly reduces the number of required wireless charging pads compared to existing methods.