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Sample-path large deviations for generalized processor sharing queues with Gaussian inputs.

机译:具有高斯输入的广义处理器共享队列的样本路径大偏差。

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摘要

Abstract In this paper we consider the generalized processor sharing (GPS) mechanism serving two traffic classes. These classes consist of a large number of independent identically distributed Gaussian flows with stationary increments. We are interested in the logarithmic asymptotics or exponential decay rates of the overflow probabilities. We first derive both an upper and a lower bound on the overflow probability. Scaling both the buffer sizes of the queues and the service rate with the number of sources, we apply Schilder's sample-path large deviations theorem to calculate the logarithmic asymptotics of the upper and lower bound. We discuss in detail the conditions under which the upper and lower bound match. Finally we show that our results can be used to choose the values of the GPS weights. The results are illustrated by numerical examples. © 2004 Elsevier B.V. All rights reserved. Keywords: Sample-path large deviations; Gaussian traffic; Schilder's theorem; Generalized processor sharing; Communication networks; Differentiated services; Weight setting
机译:摘要在本文中,我们考虑了服务于两种流量类别的通用处理器共享(GPS)机制。这些类包括大量具有平稳增量的独立的均匀分布的高斯流。我们对溢出概率的对数渐近或指数衰减率感兴趣。我们首先导出溢出概率的上限和下限。通过对队列的缓冲区大小和服务速率以及源数量进行缩放,我们应用Schilder的样本路径大偏差定理来计算上下界的对数渐近性。我们将详细讨论上限和下限匹配的条件。最后,我们证明了我们的结果可用于选择GPS权重的值。结果通过数值实例说明。 ©2004 Elsevier B.V.保留所有权利。关键字:样本路径大偏差;高斯交通;希尔德定理;通用处理器共享;通讯网络;差异化服务;重量设定

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