Abstract
In this paper we present a wavelet-based method for the analysis of data traffic exhibiting Long Range Dependence (LRD). A key element in determining network performances is the bursty nature of real traffic patterns and the estimation of the Hurst parameter H, a measure of the long term correlation level, represents a major topic in network dimensioning and management. The goal of this paper consists in analysing the statistical properties of measured traffic streams in the framework of the wavelet decomposition, not only to provide an efficient algorithm for the estimation of H, but also to investigate their behaviour at different time-scales.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Leland W.E., Taqqu M.S., Willinger W., and Wilson D.V. On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Transactions on Networking, 2 (1): 1–15, February 1994.
Erramilli A., Narayan O., and Willinger W. Experimental queueing analysis with long-range dependent packet traffic. IEEE-ACM Transactions on Networking, 4 (2): 209–223, April 1996.
Beran J. Statistics for long memory processes. Chapman&Hall, New York, 1992.
Norros I. Studies on a model for connectionless traffic, based on fractional brownian motion. In Conference on Applied Probability in Engineering, Computer and Communications Sciences, Paris, June 1993. IN- RIA/ORSA/TIMS/SMAI.
Daubechies I. Ten lectures on Wavelets, no. 61 in CBMS-NSF Series in Applied Mathematics. SIAM, Philadelphia, 1992.
Wornell G.W. Signal Processing with Fractals: a Wavelet-based approach. Signal Procesing Series. Prentice Hall, 1996.
Hess-Nielsen N. and Wickerhauser M.V. Wavelets and time-frequency analysis. Proceedings of the IEEE, 84 (4): 523–540, April 1996.
Mallat S.G. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11 (7): 674–693, July 1988.
Mandelbrot B.B. and van Ness J.W. Fractional brownian motions, fractional noises and applications. Siam Review, 10 (4): 422–437, October 1968.
Norros I. On the use of fractional brownian motion in the theory of connectionless networks. IEEE JSAC, 13: 953–962, 1995.
Wornell G.W. Wavelet-based representations for the 1/f family of fractal processes. Proceedings of the IEEE, 81 (10): 1428–1450, October 1993.
Flandrin P. Wavelet analysis and synthesis of fractional brownian motion. IEEE Transactions on Information Theory, 38 (2): 910–917, March 1992.
Abry P. and Veitch D. Wavelet analysis of long range dependent traffic, (preprint), 1996.
Giordano S., Miduri S., Pagano M., Russo F., and Tartarelli S. A wavelet- based approach to the estimation of the hurst parameter for self-similar data. In Proceedings of DSP′97, pages 479–482, July 1997.
Lau W.C., Erramilli A., Wang J.L., and Willinger W. Self-similar traffic generation: The random midpoint displacement algorithm and its properties. In Proceedings of IEEE ICC 95, pages 466–472, Seattle, June 1995.
Garroppo R.G., Miduri S., Giordano S., Pagano M., and Russo F. Statistical multiplexing of self-similar VBR videoconferencing traffic. In Proceedings of IEEE Globecom 97, Phoenix, November 1997.
Jones C.L., Lonergan G.T., and Mainwaring D.E. Wavelet packet computation of the hurst exponent. Journal of Physics A: Mathematical and General, 29: 2509–2527, 1996.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer-Verlag London Limited
About this paper
Cite this paper
Giordano, S., Pagano, M., Tartarelli, S. (1998). Analysis of the Self-Similar Characteristics of Broadband Traffic in the Wavelet Domain. In: Luise, M., Pupolin, S. (eds) Broadband Wireless Communications. Springer, London. https://doi.org/10.1007/978-1-4471-1570-0_29
Download citation
DOI: https://doi.org/10.1007/978-1-4471-1570-0_29
Publisher Name: Springer, London
Print ISBN: 978-3-540-76237-9
Online ISBN: 978-1-4471-1570-0
eBook Packages: Springer Book Archive