一种基于改进蚁群算法的选播路由算法

李领治; 郑洪源; 丁秋林

doi:10.3724/SP.J.1146.2005.00727

一种基于改进蚁群算法的选播路由算法

doi: 10.3724/SP.J.1146.2005.00727

李领治^{①②;郑洪源},
郑洪源,
丁秋林

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国家部级基金资助课题

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出版历程
- 收稿日期: 2005-06-22
- 修回日期: 2006-01-20
- 刊出日期: 2007-02-19

An Anycast Routing Based on Improved Ant Colony Algorithm

摘要

摘要: 为了在网络负载较大的情况下实现多目标多路径的选播路由，该文根据蚂蚁寻径与选播路由的相似性，提出了一种基于改进蚁群算法的选播路由算法。在运用数据包传输的历史信息来模拟路径信息素的基础上，增加了目标地址泛洪负载信息来模拟食物气味散发的过程，使得各个节点可以获得服务器和链路的最新信息。节点根据路径上的信息素、食物的气味以及链路的可见度等综合生成概率表，作为后继蚂蚁路径选择的依据。运用NS-2对该算法进行仿真，测试结果表明它可以减少传输时延，降低服务器负载的波动幅度，实现链路的负载均衡，增加网络的容量，提高选播服务的可扩展性。
- 选播;路由算法;蚁群算法;NS-2
Abstract: In order to implement multi-destination and multi-path anycast routing on the heavy load network, an anycast routing based on improved ant colony algorithm is proposed in this paper according to the similar between ant searching path and anycast routing. When the pheromone trails is simulated by the history information of the forwarded packet, it is added that the food distributing smells is simulated by the destination address flooding load information, so every node can receive the latest information of links and servers. Tables of probabilities are created by nodes based on pheromone, smell and visibility. Tables act as the basis that the succeeding ants choose the routes. This routing algorithm is simulated by NS-2. The test result indicates that it can reduce the delay of transmission, decrease the fluctuating range of severs load, implement the load-balancing of links, increase the capability of networks transmission, and improve the scalability of anycast service.

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[1] Hinden R and Deering S. Internet protocol version 6 (IPv6) addressing architecture. RFC 3513, 2003. [2] Jia W, Zhou W, and Kaiser J. Efficient algorithm for mobile multicast using anycast group[J].IEE Proc. -Communications.2001, 148(1):14-18 [3] Xuan D, Jia W, and Zhao W, et a1.. A routing protocol for anycast messages[J].IEEE Trans. on Parallel and Distributed Systems.2000, 11(6):571-588 [4] Katabi D and Wroclawski J. A framework for scalable global IP-anycast (GIA)[J].In Proc. ACM SIGCOMM 00, Stockholm.2000, 30:3-15 [5] Lin C, Lo J, and Kuo S. Load-balanced anycast routing. IEEE the 10th International Conference on Parallel and Distributed Systems, Newport Beach, 2004: 701-708. [6] Zegura E W, Ammar M H, and Fei Z, et a1.. Application-layer anycasting: A server selection architecture and use in a replicated web service[J].IEEE/ACM Trans. on Networking.2000, 8(4):455-466 [7] Dorigo M, Maniezzo V, and Colorni A. Ant system: Optimization by a colony of cooperating agents[J].IEEE Trans. on Systems, Man, and Cybernetics.1996, 26(1):29-41 [8] 段海滨, 王道波. 蚁群算法的全局收敛性研究及改进. 系统工程与电子技术, 2004, 26(10): 1056-1059. Duan Hai-bin and Wang Dao-bo. Research and improvement on the global convergence of ant colony algorithm. Systems Engineering and Electronics, 2004, 26(10): 1056-1059. [9] Lu Y, Zhao G Z, and Su F J. Adaptive ant-based dynamic routing algorithm[J].5th World Congress on Intelligent Control and Automation, Hangzhou.2004, 3:2694-2697 [10] Hsiao Y T, Chuang C L, and Chien C C. Computer network load-balancing and routing by ant colony optimization. 12th IEEE International Conference on Networks, Singapore, 2004, 1: 313-318.

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