摘要
针对无线传感器网络移动代理路由问题,提出了Q学习和蚁群优化混合的无线传感器网络移动代理路由算法。该算法综合了Q学习和蚁群优化算法思想,引入了新的路径选择概率模型,并对最优路径进行了有效的维护。仿真实验结果表明:该算法有效地提高移动代理选路效率,满足不同任务对时延的要求,增强了最优路径的可靠性,进一步降低了网络能耗。
In view of mobile Agent routing problem in Wireless Sensor Networks (WSN), a mobile Agent routing algorithm for WSN based on Q learning hybrid with ant colony optimization was proposed. A new path choosing probability model was introduced and the optimal path was efficiently maintained in the algorithm. The simulation results show that the mobile Agent routing efficiency is highly improved and delay requirements in multiple tasks are fulfilled, the reliability of the optimal path is enhanced, and network energy consumption is reduced.
出处
《计算机应用》
CSCD
北大核心
2013年第9期2440-2443,2449,共5页
journal of Computer Applications
基金
甘肃省发展和改革委员会项目(010DKB021)
关键词
无线传感器网络
Q学习
蚁群优化
移动代理
路由算法
路径维护
Wireless Sensor Network (WSN)
Q learning
ant colony optimization
mobile Agent
routing algorithm
path repair