Fast Self-Similar Network Traffic Generation Based on FGN and Daubechies Wavelets


The KIPS Transactions:PartC, Vol. 11, No. 5, pp. 621-632, Oct. 2004
10.3745/KIPSTC.2004.11.5.621,   PDF Download:

Abstract

Recent measurement studies of real teletraffic data in modern telecommunication networks have shown that self-similar (or fractal) processes may provide better models of teletraffic in modern telecommunication networks than Poisson processes. If this is not taken into account, it can lead to inaccurate conclusions about performance of telecommunication networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. A new generator of pseudo-random self-similar sequences, based on the fractional Gaussian nois and a wavelet transform, is proposed and analysed in this paper. Specifically, this generator uses Daubechies wavelets. The motivation behind this selection of wavelets is that Daubechies wavelets lead to more accurate results by better matching the self-similar structure of long range dependent processes, than other types of wavelets. The statistical accuracy and time required to produce sequences of a given (long) length are experimentally studied. This generator shows a high level of accuracy of the output data (in the sense of the Hurst parameter) and is fast. Its theoretical algorithmic complexity is O(n).


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
H. D. Jeong and J. S. Lee, "Fast Self-Similar Network Traffic Generation Based on FGN and Daubechies Wavelets," The KIPS Transactions:PartC, vol. 11, no. 5, pp. 621-632, 2004. DOI: 10.3745/KIPSTC.2004.11.5.621.

[ACM Style]
Hae Duck Jeong and Jong Suk Lee. 2004. Fast Self-Similar Network Traffic Generation Based on FGN and Daubechies Wavelets. The KIPS Transactions:PartC, 11, 5, (2004), 621-632. DOI: 10.3745/KIPSTC.2004.11.5.621.