改进遗传算法的WSN节点最优路由选择策略

计算机工程与应用 ›› 2015, Vol. 51 ›› Issue (13): 101-105.

改进遗传算法的WSN节点最优路由选择策略

刘章1，谭阳2

1.湖南广播电视大学教育信息技术中心，长沙 410004
2.湖南师范大学数学与计算机科学学院，长沙 410081

出版日期:2015-07-01 发布日期:2015-06-30

Routing selecting strategy based on improved genetic algorithm for wireless sensor networks

LIU Zhang1, TAN Yang2

1.Education Technology?Center, Hunan Radio & TV University, Changsha 410004, China
2.College of Mathematics and Computer Science, Hunan Normal University, Changsha 410081, China

Online:2015-07-01 Published:2015-06-30

摘要/Abstract

摘要： 针对无线传感器节点数据传输过程中的能量消耗问题，为了提高节点数据传输实时性，提出一种改进遗传算法的无线传感器网络节点最优路由选择策略。根据无线传感器网络的拓扑结构将监测区域划分不同大小的簇，并根据节点剩余能量选择每一个簇的簇头节点，然后将簇头节点编码成遗传算法的个体，根据数据转发能量耗能和延迟时间构建个体的适应度函数，并通过模拟自然界生物进化过程中的选择、交叉、变异等操作，找到节点数据转发的最优路径，在Matlab 2012平台上对数据路由算法的性能进行仿真测试。仿真结果表明，相对其他路由选择策略，提出的路由选择策略不仅可以均衡各个传感器节点的剩余能量，而且大幅度减少了数据转发路由过程中的能量消耗和延迟时间。

关键词: 无线传感器网络, 路由选择, 遗传算法, 簇头节点

Abstract: In view of energy consumption problem in wireless sensor nodes data transmission, in order to improve the real-
time node data transmission, this paper puts forward a routing selecting strategy of wireless sensor network based on improved genetic algorithm. The monitoring region is divided into different size clusters according to the topological structure of wireless sensor network, and head node of each cluster is selected according to the node residual energy, and then the cluster head nodes are encoded into the individual of genetic algorithm, the fitness function of individual is constructed based on energy consumption and delay time, and the optimal path node of forwarding data is found by simulating selection, crossover and mutation operator in biological natural evolution process, finally, the performance of data routing algorithm is tested on Matlab 2012 simulation platform. The simulation results show that compared with other routing strategies, the proposed routing strategy can not only balance the residual energy of each sensor node, but also greatly reduce energy consumption and delay time of the data forwarding routing process.

Key words: wireless sensor networks, routing selecting, genetic algorithm, cluster head nodes

刘章1，谭阳2. 改进遗传算法的WSN节点最优路由选择策略[J]. 计算机工程与应用, 2015, 51(13): 101-105.

LIU Zhang1, TAN Yang2. Routing selecting strategy based on improved genetic algorithm for wireless sensor networks[J]. Computer Engineering and Applications, 2015, 51(13): 101-105.

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