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计算机工程 ›› 2011, Vol. 37 ›› Issue (4): 99-101. doi: 10.3969/j.issn.1000-3428.2011.04.035

• 网络与通信 • 上一篇    下一篇

基于蚁群遗传混合算法的QoS组播路由

陈西宏,刘少伟,胡茂凯,关 娇   

  1. (空军工程大学导弹学院,陕西 三原 713800)
  • 出版日期:2011-02-20 发布日期:2011-02-17
  • 作者简介:陈西宏(1961-),男,教授、博士生导师,主研方向:组播路由;刘少伟,博士;胡茂凯、关 娇,硕士

QoS Multicast Routing Based on Ant Colony Genetic Hybrid Algorithm

CHEN Xi-hong, LIU Shao-wei, HU Mao-kai, GUAN Jiao   

  1. (Missile Institute, Air Force Engineering University, Sanyuan 713800, China)
  • Online:2011-02-20 Published:2011-02-17

摘要: 具有延迟、延迟抖动、带宽、丢包率等服务质量约束的组播路由问题具有NP完全的复杂度。基于蚁群优化算法和遗传算法,提出解决QoS约束组播路由问题的混合算法。利用遗传算法和蚁群优化算法各自的优点,使用蚁群优化算法选择种群,遗传算法优化蚂蚁遍历所得到的解。仿真实验结果表明,该算法可满足各个约束条件,且全局寻优性能好,能够满足网络服务质量要求。

关键词: 组播路由, 蚁群优化算法, 遗传算法, 服务质量

Abstract: The minimum-cost Quality of Service(QoS) multicast routing problem with delay, delay jitter, bandwidth, packet loss rate belongs to NP-complete problem, a hybrid algorithm with Ant Colony Optimization(ACO) algorithm and Genetic Algorithm(GA) is presented to solve this QoS multicast routing problem. The ACO-GA algorithm absorbs the merits of ACO and GA respectively. In hybrid algorithm, ACO is used to select the new solution. GA is used to optimize the solution generated by ACO. Test results show that the new algorithm can satisfy all the restrictions of QoS routing problem excellently, has better performance in finding global best solution and can meet the service quality requirement in real communication network.

Key words: multicast routing, Ant Colony Optimization(ACO) algorithm, Genetic Algorithm(GA), Quality of Service(QoS)

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