基于K-means聚类和蚁群算法在WSN粮情测控中的研究  

Research on monitoring and control of WSN grain condition based on K-means clustering and ant colony algorithm

作　　者：李红利[1] 赵庆明 LI Hong-li;ZHAO Qing-ming(College of Electrical Engineering and Automation,Tianjin Polytechnic University,Tianjin 300387,China)

机构地区：[1]天津工业大学电气工程与自动化学院,天津300387

出　　处：《粮食与油脂》2020年第6期73-76,共4页Cereals & Oils

摘　　要：结合无线粮情测控中粮仓环境数据采集,以及WSN(无线传感器网络)供电能量有限等特点,提出一种基于LEACH协议、K-means聚类和蚁群算法的WSN改进路由算法。首先在预处理阶段利用K-means聚类算法将散布的节点分成多个簇,通过聚类减少数据发送量。其次,利用蚁群算法支持多路径的特点,在数据传输阶段形成簇首间多跳路由机制。仿真结果表明:所用算法能够有效减少数据传输时的能量消耗,延长节点的网络生命周期。Combining the wireless grain monitoring and control environment data collection in the grain warehouse and the limited power supply of WSN(Wireless Sensor Network),an improved WSN routing algorithm based on LEACH protocol,K-means clustering and ant colony algorithm was proposed.Firstly,in the phase of pre-treatment,K-means clustering algorithm was used to divide the distributed nodes into multiple clusters and reduce the amount of data transmission through clustering.Secondly,using the ant colony algorithm to support the characteristics of multipath,a multi-hop routing mechanism was formed during the data transmission phase.Simulation results showed that the proposed algorithm could effectively reduce the energy consumption of data transmission and extend the network life cycle of nodes.

关 键 词：粮情测控 无线传感器网络 LEACH协议 K-MEANS聚类 蚁群算法 

分 类 号：TN801[电子电信—信息与通信工程]