基于分簇的WSN充电路径优化算法研究  

Study on WSN charging optimization algorithms based on clustering

作　　者：马超 汪伟 安斯光 MA Chao;WANG Wei;AN Siguang(College of Mechanical and Electrical Engineering,China Jiliang University,Hangzhou 310018,China)

机构地区：[1]中国计量大学机电工程学院,浙江杭州310018

出　　处：《中国计量大学学报》2021年第2期231-239,共9页Journal of China University of Metrology

摘　　要：目的:针对WSN电量受限问题,对WSN进行分簇并优化充电车充电路径。方法:首先,提出一种新簇首选择机制的head-K-means分簇算法,降低数据传输能耗;其次,提出一种改进的蚁群算法(MACO),将当前传感器电量加入到蚁群算法(ACO)的状态转移规则中,并且与分簇算法相结合。结果:仿真结果表明,基于分簇的充电路径优化算法在出现节点死亡时间上推迟了33%;充电车移动距离方面降低了8.2%。结论:所提出的算法能降低WSN能耗,提高充电车充电效率。Aims:Aiming at the power limited problem in WSN,we clusterd the WSN and optimized the vehicle charging path.Methods:Firstly,a new head-K-means clustering algorithm was proposed to reduce the energy consumption of data transmission.Secondly,by putting the sensor power into the state transition rule of ACO and combining with the clustering algorithm,an improved ant colony algorithm(MACO)was proposed.Results:Simulation results showed that the node death time of the optimization algorithm-based cluster charging path delayed 33%;and the moving distance of the charging vehicle reduced 8.2%.Conclusions:The proposed algorithm can reduce the energy consumption of WSN and improve the charging efficiency of the charging vehicle.

关 键 词：无线传感器网络 网络分簇 蚁群算法 充电路径优化 

分 类 号：TM393[电气工程—电机]