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Modeling spatial and temporal behavior of Internet traffic anomalies

机译:建模Internet流量异常的时空行为

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A new approach based on graph wavelets for analyzing the spatial and temporal behavior of Internet traffic anomalies is presented. This approach is applied to Internet2 traffic measurements to evaluate the time duration and spatial spread (number of links affected) of anomalies. Based on the empirical results, a node model is proposed that captures the behavior of anomalies at individual network nodes. The model considers various aspects of anomalies, such as its origin, termination, propagation, duration and volume changes. The derivation of the model parameters requires only local node information, but the model is capable of producing network-wide anomalies whose behavior mimics network wide anomalies. Model is verified by using Internet2 traffic data. Since the proposed model can be specified using only a few parameters, it can be used in place of large anomaly traces with a great data reduction. As extensions, the model is applied over a path and an aggregated model that applies to a neighborhood in the network is also presented. A method to use the graph wavelet components found during the analysis to implement a real-time anomaly monitoring system is also discussed.
机译:提出了一种基于图小波的互联网流量异常时空行为分析新方法。该方法适用于Internet2流量测量,以评估异常的持续时间和空间分布(受影响的链接数)。基于经验结果,提出了一个节点模型,该模型捕获了各个网络节点上异常的行为。该模型考虑了异常的各个方面,例如异常的起源,终止,传播,持续时间和体积变化。模型参数的推导仅需要本地节点信息,但是该模型能够产生行为类似于网络范围的异常的网络范围的异常。通过使用Internet2流量数据验证模型。由于建议的模型仅需使用几个参数即可指定,因此可以代替大量的异常迹线使用,从而大大减少了数据量。作为扩展,模型被应用在路径上,并且还提出了适用于网络中邻域的聚合模型。还讨论了一种使用分析中发现的图小波分量来实现实时异常监视系统的方法。

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