分布式网络测量中测量节点的智能选择算法

Intelligent Selection Algorithm of Measurement Nodes in Distributed Network Measurement

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。

The complexity of large-scale networks calls for monitoring techniques of special consideration. The automa- tic selection of measurement nodes must make a balance between costs and coverage. With appropriate selection of mea- surement nodes, not only the performance status of the overall network can be obtained, but also the impact of monito- ring on the monitored network in terms of bandwidth and consumption of software/hardware resources can effectively be redueed. By targeting minimum number of measurement nodes, applying ant eolony optimization as the basic algo- rithm, and making improvements and innovations on the foundation of the basic algorithm, an intelligent selection algo- rithm of measurement nodes was formed and proposed.