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Scaling Analysis of Wavelet Quantiles in Network Traffic

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Traffic Monitoring and Analysis (TMA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 5537))

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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.

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References

  1. Sarvotham, S., Riedi, R., Baraniuk, R.: Network and user driven alpha-beta on-off source model for network traffic. Computer Networks 48(3), 335–350 (2005)

    Article  Google Scholar 

  2. Giorgi, G., Narduzzi, C.: A study of measurement-based traffic models for network diagnostics. In: Proc. IEEE Instrum. Meas. Tech. Conf. IMTC 2007, Warsaw, Poland, May 01-03 (2007)

    Google Scholar 

  3. Abry, P., Taqqu, M.S., Veitch, D.: Wavelets for the analysis, estimation and synthesis of scaling data. In: Park, K., Willinger, W. (eds.) Self Similar Traffic Analysis and Performance Evaluation. Wiley, Chichester (2000)

    Google Scholar 

  4. Giorgi, G., Narduzzi, C.: Rate-interval curves: A tool for the analysis and monitoring of network traffic. Performance Evaluation 65(6-7), 441–462 (2008)

    Article  Google Scholar 

  5. Leland, W., Taqqu, M., Willinger, W., Wilson, D.: On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Trans. on Information Theory 2(1), 1–15 (1994)

    Google Scholar 

  6. Pesquet-Popescu, B.: Statistical properties of the wavelet decomposition of certain non-gaussian self-similar processes. Signal Processing 75, 303–322 (1999)

    Article  MATH  Google Scholar 

  7. National Laboratory for Applied Network Reasearch, U, http://mna.nlanr.net

  8. Stoev, S., Taqqu, M., Marron, J.: On the wavelet spectrum diagnostic for hurst parameter estimation in the analysis of internet traffic. Computer Networks 48(3), 423–445 (2005)

    Article  Google Scholar 

  9. Ivchenko, G., Medvedev, Y.: Mathematical Statistics. Mir, Moscow, Russia (1990)

    Google Scholar 

  10. Giorgi, G., Narduzzi, C.: Uncertainty of quantiles estimates in the measurement of self-similar processes. In: Proc. of inter. Workshop on Advanced Methods for Uncertainty Estimation in Measurement, AMUEM 2008, Sardagna, Trento, Italy, July 21-22 (2008)

    Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Giorgi, G., Narduzzi, C. (2009). Scaling Analysis of Wavelet Quantiles in Network Traffic. In: Papadopouli, M., Owezarski, P., Pras, A. (eds) Traffic Monitoring and Analysis. TMA 2009. Lecture Notes in Computer Science, vol 5537. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01645-5_13

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  • DOI: https://doi.org/10.1007/978-3-642-01645-5_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01644-8

  • Online ISBN: 978-3-642-01645-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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