无线可充电传感器网络能量源部署方法研究  

ENERGY SOURCE DEPLOYMENT METHOD FOR WIRELESS RECHARGEABLE SENSOR NETWORK

作　　者：於晨阳 谢志军[1] Yu Chenyang;Xie Zhijun(School of Information Science and Engineering,Ningbo University,Ningbo 315211,Zhejiang,China)

机构地区：[1]宁波大学信息科学与工程学院,浙江宁波315211

出　　处：《计算机应用与软件》2023年第5期154-159,共6页Computer Applications and Software

基　　金：宁波市国际合作项目(2016D10008);宁波市2025重点研发项目(2019B10125,2019B10028)。

摘　　要：研究无线可充电传感器网络中能量源的部署优化问题。为了获得充电效用更优的部署位置,提出一种基于混合乌鸦搜索算法和交叉算法的启发式部署方法。该算法改进了乌鸦搜索算法的随机跟随策略,并在乌鸦搜索算法基础上引入交叉算法平衡全局搜索和局部开发的能力,使用一维数组编码能量源位置代表乌鸦个体,将全网总充电效用作为适应度函数。分别在小规模部署和大规模部署场景中测试算法性能,实验结果表明,与其他启发式算法相比,该算法具有更优的搜索能力和更快的收敛速度,能够找到充电效用更优的部署位置。This paper researches the deployment optimization of energy sources in wireless rechargeable sensor networks.In order to obtain a better deployment location for charging utility,a heuristic deployment method based on hybrid crow search algorithm and crossover algorithm was proposed.This algorithm improved the random follow strategy of the crow search algorithm,and introduced a crossover algorithm based on the crow search algorithm to balance the capabilities of global search and local development.It used a one-dimensional array to encode the position of the energy source to represent the individual crow,and the total charging utility of the entire network was used as fitness function.The performance of the proposed algorithm was tested in small-scale and large-scale deployment scenarios respectively.The experimental results show that compared with other heuristic algorithms,the proposed algorithm has better search capability and faster convergence speed,and can find a better deployment location with better charging utility.

关 键 词：能量源部署 充电效用 乌鸦搜索算法 水平交叉 垂直交叉 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置] TP3[自动化与计算机技术—控制科学与工程]