An Anycast Routing Based on Improved Ant Colony Algorithm

Li Ling-zhi; Zheng Hong-yuan; Ding Qiu-lin

doi:10.3724/SP.J.1146.2005.00727

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Article Navigation > Journal of Electronics & Information Technology > 2007 > 29(2): 340-344

Li Ling-zhi, Zheng Hong-yuan, Ding Qiu-lin. An Anycast Routing Based on Improved Ant Colony Algorithm[J]. Journal of Electronics & Information Technology, 2007, 29(2): 340-344. doi: 10.3724/SP.J.1146.2005.00727

Citation:

Li Ling-zhi, Zheng Hong-yuan, Ding Qiu-lin. An Anycast Routing Based on Improved Ant Colony Algorithm[J]. Journal of Electronics & Information Technology, 2007, 29(2): 340-344. doi: 10.3724/SP.J.1146.2005.00727

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An Anycast Routing Based on Improved Ant Colony Algorithm

doi: 10.3724/SP.J.1146.2005.00727

Received Date: 2005-06-22
Rev Recd Date: 2006-01-20
Publish Date: 2007-02-19

Abstract

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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References

[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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