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Sample path moderate deviations for a family of long-range dependent traffic and associated queue length processes

机译:一系列与远程相关的流量和相关的队列长度过程的样本路径适度偏差

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摘要

We consider the long-range dependent cumulative traffic generated by the superposition of constant rate fluid sources having exponentially distributed intra start times and Pareto distributed durations with finite mean and infinite variance. We prove a sample path moderate deviation principle when the session intensity is increased and the processes are centered and scaled appropriately. The governing rate function is known from large deviation principles for the tail probabilities of fractional Brownian motion. We derive logarithmic tail asymptotics for associated queue length processes when the traffic loads an infinite buffer with constant service rate, The moderate deviation approximation of steady-state queue length tail probabilities is compared to those obtained by computer simulations.
机译:我们考虑由恒定速率流体源的叠加所产生的与远程相关的累积流量,这些恒定速率流体源具有有限的均值和无限方差的指数分布的内部开始时间和帕累托分布的持续时间。我们证明了当会话强度增加且过程集中并按比例缩放时的样本路径适度偏差原理。对于分数布朗运动的尾部概率,从大偏差原理可以知道控制率函数。当流量加载具有恒定服务速率的无限缓冲区时,我们导出了相关联的队列长度过程的对数尾部渐近线,并将稳态队列长度尾部概率的中度偏差近似与通过计算机模拟获得的结果进行比较。

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