联合无线充电与数据收集的移动充电装置多目标路径规划算法

Multi-objective path planning algorithm for mobile charging devices jointing wireless charging and data collection

针对无线传感器网络节点资源有限导致数据收集不完整和时效性差的问题,建立了联合无线充电和数据收集的移动充电装置(MCD)多目标路径规划模型,提出了一种基于贪心策略的联合无线充电和数据收集的MCD路径规划算法(PPGS)。首先,对监测区域采用基于正六边形的无缝划分策略,有效减少了MCD的访问单元数;然后,利用马尔可夫模型预测节点能量和数据采集量等参数,在此基础上预估了MCD锚点最小停留时间和最长等待时间。与现有时延受限移动式能量补充算法(DCMEC)和基于网格的移动装置调度算法(GBA+MDSA)相比,所提算法具有复杂度较低,且无需事先知道节点和锚点实际位置信息的优势。仿真结果表明:PPGS能以较少的MCD保证无线传感器网络数据收集的完整性和时效性。

The limited resources of wireless sensor network nodes cause the poor completeness and timeliness of data collection.To solve these problems,a multi-objective path planning model for Mobile Charging Devices(MCD)jointing mobile charging and data collection was established,and a Path Planning algorithm based on Greedy Strategy for MCD jointing wireless charging and data collection(PPGS)was proposed.Firstly,the monitoring area was divided into many seamless regular hexagon cells,so as to effectively reduce the number of cells visited by MCD.Then,the parameters such as the node energy and the quantity of data collection were predicted by using the Markov model,and the anchor minimum stopping time and anchor maximum waiting time for MCD were predicted based on the above.Compared with the existing Delay-Constrained Mobile Energy Charging algorithm(DCMEC)and Mobile Device Scheduling Algorithm and Grid-Based Algorithm(GBA+MDSA),the proposed algorithm has lower complexity and does not need to know the actual location information of nodes and anchors in advance.The simulation results show that,the proposed PPGS can guarantee the completeness and timeliness of data collection with a small number of MCD in wireless sensor network.