基于并行化蚁群算法的网络测量节点选取算法Network Measurement Node Selection Algorithm Based on Parallel ACO Algorithm
郝航;金跃辉;杨谈;
摘要(Abstract)：
提出了一种基于并行化蚁群算法,用于网络测量中测量节点自动选取的算法(MNS)。首先对传统蚁群算法进行改进,使其适用于网络测量中测量节点的选取场景。然后分析蚁群算法的并行化方案,设计并实现并行化框架。最后通过多元函数求解极值分析和在模拟网络中运行选点任务两种方法,对并行化选点算法(P-MNS)和非并行化选点算法进行对比。通过实验验证,并行化的蚁群算法不仅能满足网络测量节点选取的要求,同时相比非并行化算法具有更快的收敛速度,更适用于大规模网络测量。
关键词(KeyWords)： 网络测量;测量节点选择;蚁群算法;并行化框架
基金项目(Foundation): 863课题,融合网络会话控制组网、业务生成、终端管理和业务网性能监测关键技术研发(2011AA01A102)
作者(Authors): 郝航;金跃辉;杨谈;
参考文献(References)：
- [1]Jin Yue-hui.Large-scale network and business performance monitoring system V1.0[Z].Beijing University of Posts and Telecommunications,2013.
- [2]Dorigo M,Birattari M,Stutzle T.Ant colony optimization[J].IEEE Computational Intelligence Magazines,2006,1(4):36-39.
- [3]Zhu Chang-hua,Pei Chang-xing,Li Jian-dong,et al.Network measurement and its key technologies[J].Journal of Xidian University,2002,29(6):813-818.
- [4]M Dorigo,V Maniezzo,A Colorni.Ant system:optimization by a colony of cooperating agents[J].IEEE transactions on systems,man,and cybernetics.Part B,Cybernetics:a publication of the IEEE Systems,Man,and Cybernetics Society,1996,26(1):29-35.
- [5]Dorigo M,Gambardella L M.Ant colony system:a cooperative learning approach to the traveling salesman problem[J].IEEE Transactions on Evolutionary Computation,1997,1(1):53-66.
- [6]Dorigo M,Bonabeau E,Theraulaz G,Ant algorithms and stigmergy[J].Future Generation Computer Systems,2000,16(9):851-871.