Multiscale Modeling with Stable Distribution Marginals for Long-Range Dependent Network Traffic(Regular section)
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概要
- 論文の詳細を見る
As demonstrated by many studies, measured wide-area network traffic exhibits fractal properties, such as selfsimilarity, burstiness, and long-range dependence (LRD). In order to describe long-range dependent network traffic and to emphasize the performance aspects of descriptive traffic models with additive and multiplicative structures, the multifractal wavelet model (MWM), which is based on the binomial cascade, has been shown to match the behavior of network traffic over small and large time scales. In this paper, using appropriate mathematical and statistical analyses, we develop the MWM proposed in [14], which provides a complete description of long-range dependent network traffic. First, we present accurate parameters of the MWM over different time scales. Next, a marginal stable distribution of MWM network traffic data is analyzed. The accuracy of the proposed MWM compared to actual data measurements is confirmed by queuing behavior performance through computer simulations.
- 社団法人電子情報通信学会の論文
- 2002-12-01
著者
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Nguyen Chien
Department Of New Services And Automation R & D The Research Institute Of Posts And Telecoms
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Nguyen Chien
Department Of Information And Communication Engineering The University Of Electro-communications
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MIKI Tetsuya
Department of Electronic Engineering, The University of Electro-Communications
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Miki Tetsuya
Department Of Information And Communication Engineering The University Of Electro-communications
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Miki Tetsuya
Department Of Electronic Engineering The University Of Electro-communications
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