Abstract
The study of network traffic by flow analysis has been the subject of intense and varied research. Wavelet transforms, which form the core of most traffic analysis tools, are known to be robust to linear trends in data measurements, but may suffer from the presence of occasional non-stationarities. This paper considers how the information associated to quantiles of wavelet coefficients can be exploited to improve the understanding of traffic features. A tool based on these principles is introduced and results of its application to analysis of traffic traces are presented. © Springer-Verlag Berlin Heidelberg 2009.
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CITATION STYLE
Giorgi, G., & Narduzzi, C. (2009). Scaling analysis of wavelet quantiles in network traffic. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5537 LNCS, pp. 109–116). https://doi.org/10.1007/978-3-642-01645-5_13
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