In view of the stability and reliability of energy supply, distinct from the time-varying and uncertainty of energy harvesting systems, adopting mobile vehicles to replenish energy of sensors has become a research hotspot. While some existing studies on the mobile recharging problem ignored the limited energy capacity carried by mobile vehicle and the difference in energy consumption rates of sensors, in this work, we propose an adaptive real-time on-demand charging scheduling scheme that maximizes energy efficiency (CSS-MEE) for Rechargeable Wireless Sensor Networks. In CSS-MEE, we aim to achieve a compromise between maximizing charging energy efficiency and maximizing charging throughput for solving the on-demand mobile charging problem. Due to the limited energy capacity of the mobile charger, CSS-MEE uses both full-charge mode and adaptive charging mode, depending on the number of charging requests. It combines charging node selection with dispatch path feasibility determination, which takes into account the location-generated charging cost and energy-driven charging priority, to ensure the charging efficiency. Extensive simulations are conducted to demonstrate the advantages of CSS-MEE. Compared with existing approaches, simulation results show that CSS-MEE achieves better performance in terms of charging throughput, average charging latency, charge scheduling times, and charging efficiency.

中文翻译：

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一种适用于可充电无线传感器网络的自适应按需充电方案

鉴于能量供应的稳定性和可靠性，有别于能量收集系统的时变和不确定性，采用移动车辆为传感器补充能量已成为研究热点。虽然现有的一些关于移动充电问题的研究忽略了移动车辆携带的有限能量容量和传感器能量消耗率的差异，但在这项工作中，我们提出了一种最大化能源效率的自适应实时按需充电调度方案（ CSS-MEE) 用于可充电无线传感器网络。在 CSS-MEE 中，我们的目标是在最大化充电能源效率和最大化充电吞吐量之间实现折衷，以解决按需移动充电问题。由于手机充电器的能量容量有限，CSS-MEE根据充电请求的数量，采用满充模式和自适应充电模式。它将充电节点选择与调度路径可行性确定相结合，兼顾位置产生的充电成本和能量驱动的充电优先级，保证充电效率。进行了广泛的模拟以证明 CSS-MEE 的优势。仿真结果表明，与现有方法相比，CSS-MEE在充​​电吞吐量、平均充电延迟、充电调度时间和充电效率方面取得了更好的性能。