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优化能量及跳数的增强学习WSNs路由算法 被引量：2

On Dynamic Coordination of Energy and Hop in WSNs Using Reinforcement Learning Routing Algorithm
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摘要 针对无线传感网络中强化学习路由算法存在的目标单一、建立过程复杂及节点转发开销大等问题,开展了节点能量及跳数的动态协调方法研究,提出了具有反馈学习能力的动态自适应路由算法.利用局部路由信息,反馈学习邻居状态,以能量和跳数信息加权计算出路由奖励值,并更新求解Q-value值,获取最优路由策略.经实验验证及分析,算法能有效延长无线传感器网络的生命周期. In wireless sensor network,the existing reinforcement learning routing algorithm usually optimizes single goal and it＇s process of route establishment is complex.It also has problem of the node information forwarding control overhead.In this paper,a dynamic adaptive routing algorithm with feedback learning ability has been presented to balance the energy of wireless sensor network,to reduce the routing hops,and to reduce the establishment complexity.The local routing information and the method of feedback will be used in algorithm to learn neighbors＇ state;routing reward values will be obtained by weighted calculation according to the energy information and the hop counts information;the optimal routing strategy will be obtained by updating the Q-value of routing table through the Q-value update formula.
作者 李建勇 黄伟
机构地区 西南大学计算机与信息科学学院
出处 《西南师范大学学报（自然科学版）》 CAS 北大核心 2015年第10期35-40,共6页 Journal of Southwest China Normal University(Natural Science Edition)
基金 重庆市集成示范计划课题(CSTC2013jcsf 10008) "十二五"国家支撑计划课题(2012BAD35B08)
关键词 无线传感器网络 路由算法 增强学习算法 能量消耗 wireless sensor network routing algorithm reinforcement learning algorithm energy consumption
分类号 TP393 [自动化与计算机技术—计算机应用技术]
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参考文献11

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二级参考文献41

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共引文献621

同被引文献24

引证文献2

二级引证文献12

西南师范大学学报（自然科学版）
2015年 第10期

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