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Fractal and multifractal analysis of network teletraffic

Published: 22 June 2012 Publication History

Abstract

In the paper is investigated fractal and multifractal properties of the real network traffic, such as Ethernet, TCP, UDP and the simulated fractal (self-similarity) traffic based on the fractional Gaussian noise (FGN) process. The obtained results show that the modern network traffic may be better characterized by multifractal analysis, since this approach describes both local and global features of the process. The broad multifractal Legendre spectrum of TCP, UDP and Ethernet traffic indicates multifractal behavior, whereas the narrow Legendre spectrum of FGN process indicates loss of multifractality.

References

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Abry, P., D. Veitch. "Wavelet analysis of Long-Range-Dependent Traffic", IEEE Transactions on Information Theory, vol. 1998.
[2]
Leland, W., M. Taqqu. "On the self-similar nature of Ethernet traffic". IEEE/ACM Transactions on Networking, vol.47, 1993.
[3]
Mandelbrot, B., A. Fisher, and L. Calvet. "A Multifractal Model of Asset Return", Yale University, 1997. Working Parer.
[4]
Park, K. and W. Willinger. "Self-similar network traffic:an overview" in Self-similar Network traffic and Performance Evaluation, Wiley-Interscience, 2000.
[5]
Sheluhin, O., S. Smolsky, A. Osin. "Self-similar Processes in Telecommunications", John Wiley&Sons, Ltd, 2007.
[6]
Sheluhin, O. "Multifractals. Infocommunication applications" (In Russian) Goryachaya Linia Publishers, Russia, 2011.
[7]
Willinger, W., M. S. Taqqu. "Self-similarity through high-variability:Statistical analysis of Ethernet LAN traffic at the source level". IEEE/ACM Transactions on Networking, vol.5, 1993.

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  • (2019)Fractional analytics hidden in complex industrial time series data: a case study on supermarket energy use2019 1st International Conference on Industrial Artificial Intelligence (IAI)10.1109/ICIAI.2019.8850769(1-6)Online publication date: Jul-2019

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cover image ACM Other conferences
CompSysTech '12: Proceedings of the 13th International Conference on Computer Systems and Technologies
June 2012
440 pages
ISBN:9781450311939
DOI:10.1145/2383276
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 June 2012

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Author Tags

  1. Hurst parameter
  2. fractal traffic
  3. long-range dependence
  4. multifractal Legendre spectrum
  5. multifractal analysis
  6. multifractal traffic
  7. scaling function
  8. self-similar process
  9. wavelet-based estimator

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CompSysTech'12

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Overall Acceptance Rate 241 of 492 submissions, 49%

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  • (2019)Fractional analytics hidden in complex industrial time series data: a case study on supermarket energy use2019 1st International Conference on Industrial Artificial Intelligence (IAI)10.1109/ICIAI.2019.8850769(1-6)Online publication date: Jul-2019

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