【摘要】 大规模网络结构复杂,需要有针对性的网络监测方法。测量节点的自动选择必须在测量代价和覆盖范围之间进行权衡。合理地测量节点选择,能在获取全网性能状况的同时,有效减少测量给待测网络带来的带宽占用和软硬件资源消耗的影响。以最小化测量节点数量为目标,选择蚁群算法作为测量节点自动选择的基本算法,并通过对基本算法进行改进和创新,可形成一种针对分布式网络测量的测量节点智能选择算法。更多还原

【Abstract】 The complexity of large-scale networks calls for monitoring techniques of special consideration.The automatic selection of measurement nodes must make a balance between costs and coverage.With appropriate selection of measurement nodes,not only the performance status of the overall network can be obtained,but also the impact of monitoring on the monitored network in terms of bandwidth and consumption of software/hardware resources can effectively be reduced.By targeting minimum number of measurement nodes,applying ant colony optimization as the basic algorithm,and making improvements and innovations on the foundation of the basic algorithm,an intelligent selection algorithm of measurement nodes was formed and proposed.更多还原