无线传感器网络应用越来越广泛,为了解决传感器节点的能量问题,将无线充电技术应用到传感器网络中。使用无人机为传感器节点进行无线充电,但是无人机的电池容量有限,合理的规划能够让无人机以最小的充电代价获得最大的网络效用。以最小化无人机能耗为优化目标,对无人机能量消耗进行分析,将优化目标简化成最小化路径距离,并使用遗传算法对无人机规划路径。针对遗传算法不适合解决目标点多的问题,提出基于半径的聚类算法,将节点分簇,求出每个簇的充电停留点,减少目标点数目。仿真结果表明,所设计算法得到的充电路径缩短了33.52%,无人机的能量消耗降低了35.29%。
Abstract
Wireless sensor networks are more and more widely used,in order to solve the energy problem of sensor nodes,wireless charging is applied to sensor networks.UAV is used to charge sensor nodes wirelessly,but the battery capacity of UAV is limited,Reasonable path planning can make the UAV obtain the minimum charging cost and the maximum network utility.Taking minimizing the energy consumption of UAV as the optimization objective,the energy consumption of UAV is analyzed,the optimization objective is simplified to minimize the path distance,and the genetic algorithm is used to plan the path of UAV.Aiming at the problem that genetic algorithm is not suitable to solve the problem of many target points,a radius based clustering algorithm is proposed to cluster the nodes,calculate the charging residence point of each cluster and reduce the number of target points.The simulation results show that the charging path obtained by the designed algorithm is shortened by 33.52%,and the energy consumption of UAV is reduced by 35.29%.
关键词
无线传感器网络 /
路径规划 /
聚类 /
遗传算法
Key words
wireless sensor network /
path planning /
clustering /
genetic algorithm
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基金
*山西省科技重大专项支持(20191102010)。
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