基于遗传-蚁群优化算法的QoS组播路由算法设计  

Design of QoS Multicast Routing Algorithm Based on Genetic Ant Colony Optimization Algorithm

作　　者：史郑延慧 何刚[1] SHI Zheng-yan-hui;HE Gang(School of Artificial Intelligence,Beijing University of Posts and Telecommunications,Beijing 100876,China)

机构地区：[1]北京邮电大学人工智能学院,北京100876

出　　处：《科学技术与工程》2024年第11期4626-4632,共7页Science Technology and Engineering

基　　金：教育部-中国移动科研基金“人工智能”项目(教-中移2018-1)。

摘　　要：为了提高网络路由性能,提出并设计了一种基于遗传-蚁群优化算法的服务质量(quality of service,QoS)组播路由算法。首先,设计了自适应变频采集策略用于采集网络与节点信息,以此获得网络和节点的状态,为后续路由优化提供数据支持;其次,计算路径代价,将路径代价最小作为优化目标,建立QoS组播路由优化模型,并设置相关约束条件;最后,结合遗传算法和蚁群算法提出一种遗传-蚁群优化算法求解上述模型,输出最优路径,完成路由优化。实验结果表明,所提算法可有效降低路径长度与路径代价,提高搜索效率与路由请求成功率,优化后的路由时延抖动较小。In order to improve network routing performance,a QoS(quality of service)multicast routing algorithm based on genetic ant colony optimization algorithm was proposed and designed.Firstly,an adaptive frequency conversion acquisition strategy was designed to collect network and node information,in order to obtain the status of the network and nodes and provide data support for subsequent routing optimization.Secondly,the path cost was calculated,the minimum path cost as the optimization objective was set,a QoS multicast routing optimization model was established,and relevant constraints was set.Finally,a genetic ant colony optimization algorithm was proposed by combining genetic algorithm and ant colony algorithm to solve the above model,output the optimal path,and complete routing optimization.The experimental results show that the proposed algorithm can effectively reduce path length and cost,improve search efficiency and routing request success rate,and optimize the routing delay jitter.

关 键 词：遗传算法 数据采集 QoS组播路由优化 蚁群算法 路径代价 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]