Research on Optimization Algorithm of Network Resources and Paths Based on Ant Colony

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Starting with high availability of Websites, by executing load balancing strategies, the author designs and implements an optimization algorithm of network resources and paths based on ant colony. Firstly, defining resource allocation process and objective function; secondly, discussing improvements to integrated load parameters; then, focusing on analysis of principles of ants moving, updates of pheromone concentration, ants’ data structures, and algorithm flow; Finally, simulating test by MATLAB. The solutions above can provide higher reliability and availability for Web services by balancing traffic and load.

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2324-2327

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December 2012

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Zehua Zhang Xuejie Zhang.A Load Balancing Mechanism Based on Ant Colony and Complex Nerwork Theory in Open Cloud Computing Federation[R], 2010 2nd International Conference on Industrial Mechatronics and Automation:240~243

DOI: 10.1109/icindma.2010.5538385

Google Scholar

[2] R. Schoonderwoerd, O. Holland, and 1. Bruten, "Ant-like agents for load balancing in telecommunications networks," in Proc. Agents, Marina del Rey, CA, USA, p.209~216, 1997.

DOI: 10.1145/267658.267718

Google Scholar

[3] Pan Junjie, Wang Dingwei. An Ant Colony Optimization Algorithm for Multiple Travelling Salesman Problem[C]//Proc. of the 1st International Conference on Innovative Computing, Information and Control. Beijing, China: [s. n.], 2006.

DOI: 10.1109/icicic.2006.40

Google Scholar

[4] Birattari M, Pellegrini P, Dorigo M. IEEE Transactions on Evolutionary Computation, 2007, 11(6): 732~742.

Google Scholar

[5] Sim K M, Sun Wenghong. IEEE Transactions on Systems, Man and Cybernetics(Part A), 2003, 33(5): 560~572.

Google Scholar

[6] Gao Zihe, Guo Qing, Wang Ping. An Adaptive Routing Based on an Improved Ant Colony Optimiza tion in Leo Satellite Networks[C]//Proc. of Internationa l Conference on Machine Learning and Cybernetics. HongKong, China: [s. n.], 2007.

DOI: 10.1109/icmlc.2007.4370296

Google Scholar