Modeling and analysis of power-tail distributions via classical teletraffic methods
Modeling and analysis of power-tail distributions via classical teletraffic methods
复制标题
通过经典的远程交通方法对动力尾部分布进行建模和分析
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
M. Sidi
中科院分区：
文献类型：
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作者：
D. Starobinski;M. Sidi
我们提出了一种新的方法来建模和分析功率尾分布，如帕累托分布，在通信网络。我们的方法的基础是一个拟合算法，近似幂尾分布的超指数分布。该算法具有几个关键属性。首先，可以在任何期望的精度范围内实现近似。其次，拟合的超指数分布仅取决于几个参数。第三，为了在许多时间尺度上获得精确的近似，只需要少量的指数。一旦配备了一个拟合的超指数分布，我们有一个完整的框架来分析具有幂尾分布的混沌系统。我们认为GI/G/1队列与Pareto分布的服务时间，并显示我们的方法如何允许得到定量的数值结果和渐近封闭形式的结果。这一推导表明，经典的远程交通的方法可以用于分析的功率尾部分布。
We propose a new methodology for modeling and analyzing power-tail distributions, such as the Pareto distribution, in communication networks. The basis of our approach is a fitting algorithm which approximates a power-tail distribution by a hyperexponential distribution. This algorithm possesses several key properties. First, the approximation can be achieved within any desired degree of accuracy. Second, the fitted hyperexponential distribution depends only on a few parameters. Third, only a small number of exponentials are required in order to obtain an accurate approximation over many time scales. Once equipped with a fitted hyperexponential distribution, we have an integrated framework for analyzing queueing systems with power-tail distributions. We consider the GI/G/1 queue with Pareto distributed service time and show how our approach allows to derive both quantitative numerical results and asymptotic closed-form results. This derivation shows that classical teletraffic methods can be employed for the analysis of power-tail distributions.