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蚁群算法在QoS组播路由问题中的应用 被引量:3

Implementation of Ant Colony Algorithm in QoS Multicast Routing Problem
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摘要 研究了该算法在QoS组播路由问题中的应用,描述了QoS路由优化问题。基于多个不相关可加度量的QoS路由问题是NP完全问题,目前采用的方法多为启发式算法。由于蚁群算法是一种基于蚁群系统原理的、具有自组织能力的、新型的启发式优化算法,利用其能够寻找最短路径这一特性,提出了一种基于蚁群系统原理,用于解决时延和时延抖动约束问题的组播路由问题的QoS组播路由算法。该算法改进了路径选择策略,优化了信息素更新公式。仿真结果表明,该算法能够迅速、准确地找到最优解。 Most of the algorithms applied to the QoS multicast routing problem are heuristic algorithms.Ant colony algorithm is a self-organized,novel heuristic algorithm based on ant colony system principle.Utilizing its capability of searching the shortest route,proposed a QoS multicast routing algorithm based on ant colony system to solve the delay and delay variation constrained multicast routing problem.A route selecting method is improved and the information update formula is optimized.The simulation proves that...
作者 尹莹莹 孙亮
出处 《控制工程》 CSCD 2006年第S1期170-172,211,共4页 Control Engineering of China
关键词 QOS组播路由 蚁群算法 时延 时延抖动 QoS multicast routing ant colony algorithm delay delay variation
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  • 1Chen Luonan,IEEE Trans Circuits and Systems for Video Technology,1999年,46卷,8期,974页
  • 2Cavendish D,Proc Internet Mini Conference with Globcom 98,1998年
  • 3Tan Y,Proc IEEE Workshop on Neural Networks for Signal Processing,1997年,541页
  • 4Gambardella LM, Dorigo M. Ant-Q: A reinforcement learning approach to the traveling salesman problem[A]. Proceedings of ML-95, Twelfth International Conference on Machining[C]. Morgan Kaufmann, 1995.252-260.
  • 5Dorigo M, Maniezzo V, Colorni A. The Ant System: Optimization by a colony of cooperating agents[J]. IEEE Transactions on Systems, Man, and Cybermetrics , 1996,26(1):1-13.
  • 6Dorigo M, Gambardella LM. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem[J]. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 53-66.
  • 7Dorigo M, Caro GD. Ant Algorithms for Discrete Optimization[J]. Artificial Life, 1999,5(3), 137-172.
  • 8Stutzle T, Hoos HH. MAX-MIN ant system[J]. Future Generation Computer System , 2000,16(8) : 889-914.
  • 9White T, Pagurek B, Oppacher F. ASGA: Improving the Ant System by Integration with Genetic Algorithms[A]. Proceedings of the 3rd Conference on Genertic Programming (GP/SGA98)[C], 1998. 610-617.
  • 10孙文生,刘泽民.组播路由调度的神经网络方法[J].通信学报,1998,19(11):1-6. 被引量:22

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  • 1陈燕,宋玲,李陶深.基于遗传算法的求解时延约束的选播QoS路由算法[J].微电子学与计算机,2004,21(12):46-49. 被引量:17
  • 2YU Jianping,LIN Yaping,LIN Mu,YI Yeqing.Multi-Constrained Anycast Routing Based on Ant Algorithm[J].Chinese Journal of Electronics,2006,15(1):133-137. 被引量:4
  • 3李陶深,陈松乔,陈燕,陈建二,冯凌凌.一种满足带宽和时延约束的选播QoS路由算法[J].微电子学与计算机,2006,23(10):204-206. 被引量:5
  • 4李领治,郑洪源,丁秋林.一种基于改进蚁群算法的选播路由算法[J].电子与信息学报,2007,29(2):340-344. 被引量:17
  • 5Deering S,Hinden R.RFC 2460 Intemet protocol version 6 (IPv6) specification[S].Dec 1998.
  • 6Xuan D,Jia Weijia,Zhao W.Routing protocols for anycast messages[J].IEEE Transactions on Parallel and Distributed Systems,2000, 11 (6) : 571-588.
  • 7陈燕 宋玲 李陶深.基于遗传算法一种选播QoS约束路由算法.计算机工程与应用,2003,39(36):125-129.
  • 8Dorigo M,Gambardelaa L M.Ant colony system-a cooperative learning approach to the traveling saleman problem [J].IEEE .Transaction on Evolutionary Computertaton, 1997,1( 1 ) : 53-56.
  • 9Schoonderwoerd R,Holland O,Bruten J,et al.Ant based load balancing in telecommunications networks[J].Adaptive Behavior, 1997,5 (2) : 169-207.
  • 10Di Caro G,Dorigo M.AntNet:distributed stigmergetic control for communications networks[J].Joumal of Artificial Intelligence Research, 1998(9) : 317-365.

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