[1]阎新芳王晓晓冯岩.基于Q学习的无线传感网分簇拓扑控制算法[J].郑州大学学报(工学版),2015,36(02):85-88.[doi:10.3969/ j. issn.1671-6833.2015.02.019]
　YAN Xin-fang,WANG Xiao-xiao,FENG Yan,et al.A Clustering Topology Algorithm Based on Q-learning in WSN[J].Journal of Zhengzhou University (Engineering Science),2015,36(02):85-88.[doi:10.3969/ j. issn.1671-6833.2015.02.019]
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基于Q学习的无线传感网分簇拓扑控制算法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
36卷
期数:
2015年02期
页码:
85-88
栏目:
出版日期:
2015-04-30

文章信息/Info

Title:
A Clustering Topology Algorithm Based on Q-learning in WSN
作者:
阎新芳1王晓晓2冯岩3
郑州大学信息工程学院，河南郑州450001
Author(s):
YAN Xin-fang; WANG Xiao-xiao; FENG Yan; YAN Jing-jing
School of Information Engineering,Zhengzhou University ,Zhengzhou 450001,China
关键词:
无线传感器网络; oWA ;  Q学习
Keywords:
wireless sensor network ; Ordered Weighted Average( OWA) operator ;  Q-learning
分类号:
TP393
DOI:
10.3969/ j. issn.1671-6833.2015.02.019
文献标志码:
A
摘要:
为了延长大规模无线传感器网络的生命周期,在ETBG算法的基础上提出基于Q学习的分簇拓扑控制算法.该算法利用有序加权平均(OWA)算子多属性决策的方法确定节点的权值,利用Q学习算法对节点进行周期性的学习训练,按照每条路径的Q值进行最优路径的选择,然后就可以实现网络的拓扑控制.仿真分析表明,基于Q学习算法形成的簇树机制解决了ETBG算法在生成簇树过程中未能寻找到最佳路径而造成数据传输时能量损耗过多的问题,从而达到延长网络生命周期的目的.
Abstract:
To prolong the lifetime of wireless sensor network,a Clustering Topology Algorithm Based on Q-learning in WSN ( CTQL)is proposed on the basis of classical clustering algorithms such as ETBG. The Or-dered Weighted Average ( OWA) operator multi-attribute decision making method is used to determine theweight of the nodes, and Q learning algorithm is used to periodically train the cluster heads.So the Q value ofthe optimal path is selected of this algorithm and the topology control is realized. Through simulation studyshows that the use of Q-learning algorithm to resolve the problem that much energy consumption of ETBG algo-rithm fails to find the best path and CTQL effectively extend the network lifetime.

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