Priority queues with Gaussian input: a path-space approach to loss and delay asymptotics.
Priority queues with Gaussian input: a path-space approach to loss and delay asymptotics.
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发表时间：
2005
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通讯作者：
M. Mandjes;P. Mannersalo;I. Norros
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作者：
M. Mandjes;P. Mannersalo;I. Norros
优先级分配是为基于分组的网络提供实时服务质量的基本技术。然而，一般的交通模型的优先级队列的数学分析是非常困难的，特别是当交通是长距离依赖。本文件提出了朝这一方向迈出的一些重要步骤。我们的分析是第一次数学上严格的处理路径空间的大偏差的优先级队列类明智的异构高斯输入具有任意的相关结构。这包括计算导致其中一个队列溢出的最可能路径。与以前的工作相比，同一主题，本文提供了三个新的贡献：一个新的表示在低优先级队列中的工作量，最可能的路径的精确表征，以及扩展的分析虚拟等待时间，除了队列长度。
Priority queueing is the basic technique for providing real-time Quality of Service to packet-based networking. The mathematical analysis of priority queues with general traffic models is, however, prohibitively difficult, in particular when the traffic is long-range dependent. This paper provides some important steps forward in this direction. Our analysis is the first mathematically rigorous treatment of path-space large deviations of priority queues with class-wise heterogeneous Gaussian input having an arbitrary correlation structure. This includes the computation of the most probable paths that lead to overflow in one of the queues. Compared with earlier work on the same topic, the paper provides three novel contributions: a new representation of the workload in the low-priority queues, an exact characterization of the most probable paths, and an extension of the analysis to virtual waiting times, in addition to queue lengths.