[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]
点击复制

基于Q学习的无线传感网分簇拓扑控制算法()
分享到：

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
36
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.

相似文献/References:

[1]冯冬青邢凯丽.基于能量平衡的无线传感网络分布式成簇机制[J].郑州大学学报(工学版),2015,36(03):6.[doi:10.3969/ j. issn.1671 -6833.2015.03.002]
　FENG Dong-qing,XING Kai-li.A Distributed Clustering Mechanism Based on Energy Balancein Wireless Sensor Networks[J].Journal of Zhengzhou University (Engineering Science),2015,36(02):6.[doi:10.3969/ j. issn.1671 -6833.2015.03.002]
[2]严晶晶,阎新芳,冯岩.WSN中基于梯度和粒子群优化算法的分级簇算法[J].郑州大学学报(工学版),2016,37(02):33.[doi:10.3969/j.issn.1671-6833.201505017]
　Yan Xinfang,Yan Jingjing,Feng Yan.Gradient and Particle Swarm Optimization Based Hierarchical Cluster Algorithm in WSN[J].Journal of Zhengzhou University (Engineering Science),2016,37(02):33.[doi:10.3969/j.issn.1671-6833.201505017]
[3]滕志军,郭力文,吕金玲,等.基于时序信息分析的WSN贝叶斯信誉评价模型[J].郑州大学学报(工学版),2019,40(01):38.[doi:10.13705/j.issn.1671-6833.2019.01.007]
　Teng Zhijun,Guo Liwen,Lu Jinling,et al.WSN Bayes Reputation Evaluation Model Based on Time Series Information Analysis[J].Journal of Zhengzhou University (Engineering Science),2019,40(02):38.[doi:10.13705/j.issn.1671-6833.2019.01.007]
[4]申金媛,赵旭东,刘润杰,等.一种无线传感器网络分层拓扑推断算法[J].郑州大学学报(工学版),2011,32(03):111.[doi:10.3969/j.issn.1671-6833.2011.03.027]
[5]凡高娟,侯彦娥,王汝传..基于RSSI参数纠正的无线传感器网络应急救灾系统[J].郑州大学学报(工学版),2012,33(04):94.[doi:10.3969/j.issn.1671-6833.2012.04.022]
　FAN Gaojuan,HOU Yane,WANG Ruchuan.RSSI based Parameters Correction Emergency Disaster Response Systemof Wireless Sensor Networks[J].Journal of Zhengzhou University (Engineering Science),2012,33(02):94.[doi:10.3969/j.issn.1671-6833.2012.04.022]

更新日期/Last Update: