Skip to main content
SpringerLink
Log in

Hurst parameter estimation by wavelet transformation and a filter bank for self-similar traffic

  • Published:
Automatic Control and Computer Sciences Aims and scope Submit manuscript

Abstract

A model of traffic generation with the preset Hurst parameter (self-similarity) followed by its estimation in Matlab using wavelet transformation and a filter banks is described. The error in estimating the given parameter is analyzed depending on the value of this parameter and the number of wavelet transformation scales used in the estimation procedure. This study is experimental, aimed at real-time estimation of the Hurst parameter and the accuracy of this estimation in the case of wavelet transformation with the help of filter banks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Leland, W., Taqqu, M., Willinger, W., and Wilson, D., On the self-similar nature of Ethernet traffic, IEEE/ACM Trans. Networking, 1994, vol. 2, no. 1, pp. 203–213.

    Article  Google Scholar 

  2. Sheluhin, O., Smolskiy, S., and Osin, A., Self-Similar Processes in Telecommunications, Wiley, 2007.

    Book  Google Scholar 

  3. Amin, F., Mizanain, K., and Mirjalily, G., Active queue management for self-similar network traffic, Electrical Engineering (ICEE), 2013 21st Iranian Conf., 2013, pp. 1–5.

    Google Scholar 

  4. de Brito, G.M., Velloso, P.B., and Moraes, I.M., Information Centric Networks: A New Paradigm for the Internet, Wiley-ISTE, 2013.

    Book  Google Scholar 

  5. Chaudhari, S.S. and Biradar, R.C., Resource prediction based routing using wavelet neural network in mobile ad-hoc networks, Circuits, Communication, Control and Computing (I4C), 2014 International Conference, 2014, pp. 273–276.

    Google Scholar 

  6. Vybornova, A. and Koucheryavy, A., Ubiquitous sensor networks traffic models for medical and tracking applications, 12th Int. Conf. on Next Generation Wired/Wireless Networking NEW2AN 2012, Saint-Petersburg, 2012.

    Google Scholar 

  7. Barreto, P.S. and de Carvalho, P.H.P., Hybrid traffic model for multimedia network performance evaluation, Advanced Information Networking and Applications, Workshops, AINAW 2008, 22nd Int. Conf., 2008, pp. 80–85.

    Google Scholar 

  8. Grab, E. and Sarkovskis, S., Real-time estimation of traffic self-similarity parameter in Simulink with wavelet transform, in Electronics and Electrical Engineering., Kaunas: Technologija, 2013.

    Google Scholar 

  9. Strang, G. and Ngueyen, T., Wavelets and Filter Banks, Wellesley: Wellesley-Cambridge Press, 1996.

    MATH  Google Scholar 

  10. Abry, P. and Veitch, D., Wavelet analysis of Long-Range-Dependent Traffic, IEEE Trans. Inf. Theory, 1998, vol. 44, no. 1, pp. 2–15.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Riga Technical University, ul. Lomonosova 1, Riga, LV-1019, Latvia

    E. Grab & E. Petersons

Authors
  1. E. Grab
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. Petersons
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to E. Grab.

Additional information

Original Russian Text © E. Grab, E. Petersons, 2015, published in Avtomatika i Vychislitel’naya Tekhnika, 2015, No. 5, pp. 47–56.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Grab, E., Petersons, E. Hurst parameter estimation by wavelet transformation and a filter bank for self-similar traffic. Aut. Control Comp. Sci. 49, 286–292 (2015). https://doi.org/10.3103/S0146411615050041

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0146411615050041

Keywords

Search

Navigation