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On use of the alpha stable self-similar stochastic process to model aggregated VBR video traffic

机译:使用alpha稳定的自相似随机过程对汇总的VBR视频流量进行建模

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摘要

The alpha stable self-similar stochastic process has been proved an effective model for high variable data traffic. A deep insight into some special issues and considerations on use of the process to model aggregated VBR video traffic is made. Different methods to estimate stability parameter α and self-similar parameter H are compared. Processes to generate the linear fractional stable noise (LFSN) and the alpha stable random variables are provided. Model construction and the quantitative comparisons with fractional Brown motion (FBM) and real traffic are also examined. Open problems and future directions are also given with thoughtful discussions.
机译:α稳定的自相似随机过程已被证明是用于高可变数据流量的有效模型。深入了解了一些特殊问题,并考虑了使用该过程对汇总的VBR视频流量进行建模的注意事项。比较了估计稳定性参数α和自相似参数H的不同方法。提供了生成线性分数稳定噪声(LFSN)和alpha稳定随机变量的过程。还检查了模型的构建以及分数布朗运动(FBM)和实际交通量的定量比较。还进行了深思熟虑的讨论,提出了未解决的问题和未来的方向。

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