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Diagnosing Network-wide Traffic Anomalies by Anukool Lakhina; Mark Crovella; Christophe Diot is a scholarly article available to read on EtoBox.

What is Diagnosing Network-wide Traffic Anomalies about?

Anomalies are unusual and significant changes in a network's traffic levels, which can often span multiple links. Diagnosing anomalies is critical for both network operators and end users. It is a difficult problem because one must extract and interpret anomalous patterns from large amounts of high-dimensional, noisy data.In this paper we propose a general method to diagnose anomalies. This method is based on a separation of the high-dimensional space occupied by a set of network traffic measurements into disjoint subspaces corresponding to normal and anomalous network conditions. We show that this separation can be performed effectively by Principal Component Analysis.Using only simple traffic measurements from links, we study volume anomalies and show that the method can: (1) accurately detect when a volume anomaly is occurring; (2) correctly identify the underlying origin-destination (OD) flow which is the source of the anomaly; and (3) accurately estimate the amount of traffic involved in the anomalous OD flow.We evaluate the method's ability to diagnose (i.e., detect, identify, and quantify) both existing and synthetically injected volume anomalies in real traffic from two bac

Author

Anukool Lakhina; Mark Crovella; Christophe Diot

Publisher

ACM

Published

2004

Language

EN