基于粒子群算法的生猪养殖物联网节点部署优化研究  

Optimization of Pig Breeding WSN Deployment Based on PSO Algorithm

作　　者：朱虹[1] 李爽[1] 郑丽敏[1,2] 杨璐[1] 

机构地区：[1]中国农业大学信息与电气工程学院,北京100083 [2]中国农业大学食品质量与安全北京实验室,北京100083

出　　处：《农业机械学报》2016年第5期254-262,共9页Transactions of the Chinese Society for Agricultural Machinery

基　　金：'十二五'国家科技支撑计划项目(2012BAD28B02);'十二五'农村领域国家科技支撑计划项目(2014BAD04B05);生猪产业技术体系北京市创新团队项目(BAIC02-2016)

摘　　要：要构建有效稳定的生猪养殖物联网系统,无线传感器网络的覆盖率和连通性是网络节点部署中需要考虑的2个关键问题。采用粒子群算法结合虚拟力算法提高网络覆盖率,通过增加节点的方式提高网络连通性。以生猪养殖场物联网系统中节点部署为应用实例,以猪舍墙壁作为主要障碍物进行部署优化,仿真结果显示虚拟力导向的粒子群算法可提高网络覆盖率15%,而提升连通性只需增加10个节点,网络性能得到了明显改善。To build a stable and effective internet of things system of pig breeding,coverage rate and connectivity of wireless sensor network are two key problems for node deployment. Obstacles have some effects on the wireless communication. The pig farm was used as an example for modeling and the piggery wall was considered as the obstacle. The sensor node＇s communication radius was decreased with the logdistance path loss model when obstacle was blocking the wireless signal. To improve the coverage rate in situation of obstacles with particle swarm optimization（ PSO） algorithm combined with virtual force was the aim. Besides,PSO algorithm can find the best positions in the network to add extra nodes for improving connectivity until all nodes get together. Matlab was used to do simulation experiments; the results showed that the virtual force-directed PSO algorithm has good performance on global optimization and convergence rate. In situation of obstacles and communication radius decreasing,the coverage rate was improved about 15% with only adding 10 nodes,which make the whole network connective.

关 键 词：生猪 物联网 无线传感器网络 节点部署 粒子群算法 

分 类 号：TP393.1[自动化与计算机技术—计算机应用技术]