The constant increase in the complexity of data networks motivates the search for strategies that make it possible to reduce current monitoring times. This paper shows the way in which multilayer network representation and the application of multiscale analysis techniques, as applied to software-defined networks, allows for the visualization of anomalies from "coarse views of the network topology". This implies the analysis of fewer data, and consequently the reduction of the time that a process takes to monitor the network. The fact that software-defined networks allow for the obtention of a global view of network behavior facilitates detail recovery from affected zones detected in monitoring processes. The method is evaluated by calculating the reduction factor of nodes, checked during anomaly detection, with respect to the total number of nodes in the network.

翻译：数据网络的复杂程度不断提高,促使人们寻找能够减少当前监测时间的战略。本文件说明了多层网络的分布方式和多尺度分析技术的应用方式,这些技术适用于软件界定的网络,使得从“网络地形图示的粗略观点”中可以直观地看到异常现象。这意味着分析较少的数据,从而缩短了监测网络的程序所需的时间。软件界定的网络允许对网络行为进行全球观察,这一事实有助于从监测过程中发现的受影响地区详细恢复。该方法通过计算节点的减少系数来评估,在发现异常时加以检查,以计算网络节点的总数。