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Loss behavior of an Internet router with self-similar input traffic via Fractal point process

机译:互联网路由器通过分形点过程具有自相似输入流量的丢失行为

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It has been reported that modeling a self-similar network traffic is of key importance for the traffic engineering. Self-similarity or long range dependence causes degradation of Internet router performance. Therefore, it is decisive for an appropriate buffer design of a router. In this paper, we investigate loss behaviour of network router with pseudo self-similar traffic input. We use Fractal point process (FPP) as input process as it generates self-similar traffic. For queueing analysis, input process is Markov modulated Poission process (MMPP), which is fitted for FPP by equating the second-order statistics of counting function. The reason is, FPP is not suitable for queueing based performance evaluation. FPP involves another parameter fractal onset time (FOT) besides Hurst parameter. Effect of FOT on loss behavior is examined.
机译:据报道,建模自相似的网络流量对交通工程来说是重要的重要性。自相似性或长距离依赖性导致互联网路由器性能的降级。因此,它是对路由器的适当缓冲设计的决定性。在本文中,我们调查了具有伪自相似流量输入的网络路由器的损耗行为。我们使用分形点处理(FPP)作为输入过程,因为它产生自相似流量。为了排队分析,输入过程是Markov调制拓扑过程(MMPP),通过等同于计数函数的二阶统计来安装FPP。原因是,FPP不适合排队的绩效评估。除了HURST参数之外,FPP还涉及另一个参数分形起始时间(FOT)。检查FOT对损失行为的影响。

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