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Modeling and analysis of self-similar traffic source based on fractal-binomial-noise-driven Poisson process

Modeling and analysis of self-similar traffic source based on fractal-binomial-noise-driven Poisson process
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摘要 This article explores the short-range dependence (SRD) and the long-range dependence (LRD) of self-similar traffic generated by the fractal-binomial-noise-driven Poisson process (FBNDP) model and lays emphasis on the former. By simulation, the SRD decaying trends with the increase of Hurst value and peak rate are obtained, respectively. After a comprehensive analysis of accuracy of self-similarity intensity, the optimal range of peak rate is determined by taking into account the time cost, the accuracy of self-similarity intensity, and the effect of SRD. This article explores the short-range dependence (SRD) and the long-range dependence (LRD) of self-similar traffic generated by the fractal-binomial-noise-driven Poisson process (FBNDP) model and lays emphasis on the former. By simulation, the SRD decaying trends with the increase of Hurst value and peak rate are obtained, respectively. After a comprehensive analysis of accuracy of self-similarity intensity, the optimal range of peak rate is determined by taking into account the time cost, the accuracy of self-similarity intensity, and the effect of SRD.
出处 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2006年第3期61-64,共4页 中国邮电高校学报(英文版)
基金 This study is supported by National Natural Science Foundation of China(60507007,60372100).
关键词 fractal-binomial-noise-driven Poisson process short-range dependence long-range dependence self similarity fractal-binomial-noise-driven Poisson process, short-range dependence, long-range dependence, self similarity
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