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Volume 25 Issue 1
Jan.  2003
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Li Yongli, Liu Guizhong, Wang Haijun, Shang Zhaowei. ON WAVELET-BASED METHODS FOR HURST INDEX ESTIMATION OF SELF-SIMILAR TRAFFIC[J]. Journal of Electronics & Information Technology, 2003, 25(1): 100-105.
Citation: Li Yongli, Liu Guizhong, Wang Haijun, Shang Zhaowei. ON WAVELET-BASED METHODS FOR HURST INDEX ESTIMATION OF SELF-SIMILAR TRAFFIC[J]. Journal of Electronics & Information Technology, 2003, 25(1): 100-105.

ON WAVELET-BASED METHODS FOR HURST INDEX ESTIMATION OF SELF-SIMILAR TRAFFIC

  • Received Date: 2001-08-14
  • Rev Recd Date: 2002-02-15
  • Publish Date: 2003-01-19
  • Existing wavelet methods for the estimation of the Hurst parameter of self-similar traffic are systematically analyzed and examined. The effects of wavelet functions, vanishing-moments and wavelet decomposition levels on the results of wavelet methods for acquiring the Hurst index are investigated via numerical experiments. Some useful conclusions are drawn on the relationship between the accuracy of the methods and the selection of the order of vanishing moments and the selection of wavelet functions.
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  • W.E. Leland, M. S. Taqqu, W. Willinger, D. V. Wilson, On the self-similar nature of Ethernet traffic (extended version), IEEE/ACM Trans. on Networking, 1994, 2(1), 1-15.[2]J. Beran, R. Sherman, M. S.Taqqu, W. Willinger, Long range dependence in variable bit rate video traffic, IEEE Trans. on Communication, 1995, 43(2/3/4), 1566-1579.[3]P. Abry, D. Veitch, Wavelet analysis of long-range dependent traffic, IEEE Trans. on Information Theory, 1998, 44(1), 2-15.[4]Z. Sahinoglu, S. Tekinay, Multiresolution decomposition and burstiness analysis of traffic traces,Wireless Communications and Networking Conference, WCNC. New Orleans, LA, USA, IEEE,Vol.2, 1999, 560-563.[5]P. Abry, P. Goncalves, P. Flandrin, Wavelet-based spectral analysis of 1/f process, IEEE International Conference on Acoustics, Speech, and Signal Processing, Minneapolis, MN, USA, Vol.3,1993, 237-240.[6]G. Wornell, Signal Processing with Fractal: A Wavelet Based Approach, Prentice Hall, Znc. NJ,1995, 30-57.[7]B. Tsybakov, N. D. Georganas, On self-similar traffic in ATM queues: Definitions, overflow probability bound, and cell delay distribution, IEEE/ACM Trans. on Networking, 1997, 5(3),397-409.[8]S. Giordano, S. Miduri, M. Pagano, F. Russo, S. Tartarelli, A wavelet-based approach to the estimation of the Hurst parameter for self-similar data, International Conference on Digital Signal Processing, DSP 97, Santorini, Greece, Vol.2, 1997, 479-482.Z. Fan, P. Mars, Self-similar traffic generation and parameter estimation using wavelet transform,IEEE Global Telecommunications Conference, Phoenix, AZ, USA, Vol.3, 1997, 1419-1423.[9]Oliver Rose, Statistical properties of MPEG video traffic and their impact on traffic modeling in ATM systems. Proc. of the 20th Annual Conference on Local Computer Networks, Minneapolis,MN, 1995, 397-406.
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