Scaling Analysis of Wavelet Quantiles in Network Traffic

Authors:
Giada Giorgi;Claudio Narduzzi
Affiliations:
Dept. of Information Engineering, University of Padova, Padova, Italy I-35100;Dept. of Information Engineering, University of Padova, Padova, Italy I-35100
Venue:
TMA '09 Proceedings of the First International Workshop on Traffic Monitoring and Analysis
Year:
2009

Citing 4
Cited 0

Statistical properties of the wavelet decomposition of certain non-Gaussian self-similar processes

Signal Processing
Rate-interval curves - A tool for the analysis and monitoring of network traffic

Performance Evaluation
On the wavelet spectrum diagnostic for Hurst parameter estimation in the analysis of Internet traffic

Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Network and user driven alpha-beta on-off source model for network traffic

Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic

Quantified Score

Hi-index	0.00

Visualization

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.