With the advancement of wireless energy transfer, Wireless Rechargeable Sensor Networks (WRSNs) have become increasingly popular for efficiently charging sensor nodes. In WRSNs, determining the charging schedule for Mobile Chargers (MCs) is critical for reducing maintenance costs and improving charging efficiency. This is termed the Charging Scheduling Problem (CSP), which is proven to be NP-hard in nature. The existing schemes lack a comprehensive approach to determine the optimal number of MCs and often set a fixed charging threshold for the sensor nodes, degrading charging efficiency in dynamic networks. Additionally, relying on a single MC is unrealistic and impractical for large-scale networks, necessitating a more advanced charging strategy. Thus, this study proposes a dynamic and multi-node charging scheduling scheme named Partitioning-based Charging Schedule for Multiple Mobile Chargers (PCSMMC). The PCSMMC utilizes the traffic load of sensor nodes and energy load of MCs to estimate the optimal number of MCs and computes the progressive threshold for sensor nodes to improve the charging efficiency. Moreover, potential sojourn locations are determined and multiple network factors are integrated into a multi-attribute decision-making process to achieve an efficient charging scheduling and path planning scheme for multiple MCs. The objective of PCSMMC is to enhance the survivability rate of sensor nodes and decrease the traveling path followed by MCs to charge the sensor nodes within the network. Empirical simulation results confirm the superiority of PCSMMC in terms of charging response time, survivability rate, energy utilization efficiency, and network lifetime by a significant margin when compared to alternative approaches.

中文翻译：

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多MC按需无线可充电传感器网络的动态充电调度和路径规划方案


随着无线能量传输的进步，无线可充电传感器网络（WRSN）对于高效充电传感器节点变得越来越流行。在 WRSN 中，确定移动充电器 (MC) 的充电时间表对于降低维护成本和提高充电效率至关重要。这被称为充电调度问题（CSP），它被证明本质上是 NP 困难的。现有方案缺乏综合方法来确定最佳 MC 数量，并且通常为传感器节点设置固定的计费阈值，从而降低了动态网络中的计费效率。此外，对于大规模网络来说，依靠单个MC是不现实和不切实际的，需要更先进的计费策略。因此，本研究提出了一种动态多节点充电调度方案，称为基于分区的多个移动充电器的充电调度（PCSMMC）。 PCSMMC利用传感器节点的流量负载和MC的能量负载来估计最佳MC数量，并计算传感器节点的渐进阈值，以提高充电效率。此外，确定潜在的停留位置，并将多个网络因素整合到多属性决策过程中，以实现多个MC的高效充电调度和路径规划方案。 PCSMMC的目标是提高传感器节点的生存率并减少MC为网络内的传感器节点充电所遵循的行进路径。经验仿真结果证实，与其他方法相比，PCSMMC 在充电响应时间、生存率、能源利用率和网络寿命方面具有显着的优势。