Wavelet Multifractal Modeling for Network Traffic and Queueing Analysis

Authors:
Xing Lu;Ke Wang;Huijing Dou
Affiliations:
-;-;-
Venue:
ICCNMC '01 Proceedings of the 2001 International Conference on Computer Networks and Mobile Computing (ICCNMC'01)
Year:
2001

Citing 5
Cited 0

Ten lectures on wavelets

Ten lectures on wavelets
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Wide area traffic: the failure of Poisson modeling

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Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level

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Wavelet analysis of long-range-dependent traffic

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Abstract

In this paper, we give a wavelet-based model of network traffic, which exhibits multifractalcharacter. The discovery of the multifractal nature of traffic has made new models and analysis tools for traffic essential, since self-similar or long-range Dependence (LRD) models are far too optimistic in their predictions of performance. Short-range Dependence (SRD) is must be considered especially in flow control (FC) and CRC design. We find that the wavelet-based model can capture important fractal properties like multi-scale variability and bursting that deleteriously affect performance. Experiments and queuing analysis is performed and the results show that the model is matched well with the real data.