改进遗传算法的电力通信网络路由优化研究  

Research on Routing Optimization of Power Communication Network Based on Improved Genetic Algorithm

作　　者：贺军 He Jun(Shaanxi Electric Power Company,Xi'an 710048,China)

机构地区：[1]陕西省电力公司

出　　处：《单片机与嵌入式系统应用》2020年第1期86-89,共4页Microcontrollers & Embedded Systems

摘　　要：针对电力通信网络对时延、可靠性等的要求,在树状拓扑网络结构基础上,提出一种基于蚁群遗传的混合动态路由算法。采用最效传输时延和丢包率作为优化目标算法,根据多路径路由方式,保留蚁群算法的备选路径,避免通信网络时变性造成路径失效,并根据信息素含量确定不同优先级。最后选择传输时延率、丢包率和吞吐量作为评价指标,对比分析了混合路由算法、遗传算法和分簇路由算法性能。结果表明:本文提出的混合路由算法具有较低的丢包率和较高的吞吐量,由于采用了备选路径,传输时延存在一定幅度上升。In order to meet the requirements of delay and reliability in power communication networks,a hybrid dynamic routing algorithm based on ant colony genetic algorithm is proposed on the basis of tree topological network structure.The most efficient transmission delay and packet loss rate are used as the optimization objective algorithm.According to the multi-path routing mode,the alternative path of ant colony algorithm is retained to avoid path failure caused by time-varying communication network,and different priorities are determined according to the pheromone content.Finally,the transmission delay rate,packet loss rate and throughput are selected as evaluation indexes.Performance of hybrid routing algorithm,genetic algorithm and clustering routing algorithm.The experiment results show that the hybrid routing algorithm proposed in this paper has low packet loss rate and high throughput.In terms of transmission delay,due to the use of alternative paths,the transmission delay increases to a certain extent.

关 键 词：电力通信网络 蚁群遗传算法 时延 丢包率 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]