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A spectral theory approach for extreme value analysis in a tandem of fluid queues

机译:串联流体队列中极值分析的频谱理论方法

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We consider a model to evaluate performance of streaming media over an unreliable network. Our model consists of a tandem of two fluid queues. The first fluid queue is a Markov modulated fluid queue that models the network congestion, and the second queue represents the play-out buffer. For this model the distribution of the total amount of fluid in the congestion and play-out buffer corresponds to the distribution of the maximum attained level of the first buffer. We show that, under proper scaling and when we let time go to infinity, the distribution of the total amount of fluid converges to a Gumbel extreme value distribution. From this result, we derive a simple closed-form expression for the initial play-out buffer level that provides a probabilistic guarantee for undisturbed play-out.
机译:我们考虑一个模型来评估不可靠网络上流媒体的性能。我们的模型由两个流体队列串联而成。第一流体队列是对网络拥塞进行建模的马尔可夫调制流体队列,第二队列代表播出缓冲区。对于此模型,拥塞和播出缓冲区中的流体总量的分布对应于第一缓冲区的最大达到水平的分布。我们表明,在适当的缩放比例下,当我们让时间达到无穷大时,流体总量的分布会收敛为Gumbel极值分布。从该结果中,我们为初始播出缓冲区级别导出了一个简单的封闭式表达式,该表达式为无扰动的播出提供了概率保证。

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