刘伯红, 赵浚尧, 王刚, 阎英. 云环境下基于改进蚁群算法的网络路由优化[J]. 微电子学与计算机, 2013, 30(1): 24-27.
引用本文: 刘伯红, 赵浚尧, 王刚, 阎英. 云环境下基于改进蚁群算法的网络路由优化[J]. 微电子学与计算机, 2013, 30(1): 24-27.
LIU Bo-hong, ZHAO Jun-yao, WANG Gang, YAN Ying. Network Routing Optimization in Cloud Based on Improved Ant Colony Algorithm[J]. Microelectronics & Computer, 2013, 30(1): 24-27.
Citation: LIU Bo-hong, ZHAO Jun-yao, WANG Gang, YAN Ying. Network Routing Optimization in Cloud Based on Improved Ant Colony Algorithm[J]. Microelectronics & Computer, 2013, 30(1): 24-27.

云环境下基于改进蚁群算法的网络路由优化

Network Routing Optimization in Cloud Based on Improved Ant Colony Algorithm

  • 摘要: 针对云计算多元化复杂的网络结构环境,提出一种旨在改善网络路由的蚁群优化算法.新算法在原有蚁群算法智能寻优的基础上,加入网络节点在网审查机制,实时判断网络节点是否在网,选择最优解路径.仿真实验表明,改进算法能有效的改善因为网络节点在网情况的多变性而造成的部分路径失效的情况,进而缓解网络拥塞.

     

    Abstract: In order to shorten the mean fault isolation time,the fault isolation strategy based on dynamic entropy search is proposed in this paper on the basis of entropy-directed algorithm and entropy-indirected algorithm.The strategy takes the maximum dynamic-entropy of the system for account to select tests and establishes fault isolation decision tree using ergodic search on the centre of dynamic entropy.It is showed by algorithm example that the strategy in this paper needs less tests and mean fault isolation time than entropy-directed algorithm and entropy-indirected algorithm.

     

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