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出 处:《仪表技术与传感器》2017年第10期105-109,共5页Instrument Technique and Sensor
基 金:国家自然科学基金项目(61501264)
摘 要:大规模无线传感器网络节点数量多、部署范围广、数据传输时延长。针对上述问题,提出移动多Sink生物超启发式路径规划算法,采用蚁群优化作上层算子,根据网络运行过程中的变化,即节点数量和能量变化,实时优选下层算子集,选中的下层算子集规划各移动Sink节点的路径。仿真研究表明,所提算法有效解决多Sink节点的路径规划问题,减小网络时延。Large-scale wireless sensor networks contained a number of nodes which distributed widely,and long delay of data transmission. In view of the above problems,this paper presented a tour planning in large-scale wireless sensor network for multiple mobile sinks based on biological hyper-heuristic,ant colony optimization was used as the high level operator. In the process of network operation,according to the changes of the number of nodes and the energy of nodes,the high level operator was real-time selected,the low level operator which was selected planned the tour of each mobile sink node. The simulation results shows that the proposed algorithm can effectively solve the tour planning problem for multi sink nodes and reduce delay.
关 键 词:大规模无线传感器网络 多Sink节点 Sink节点移动 生物超启发式 路径规划
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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