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Stochastic decomposition in discrete-time queues with generalized vacations and applications

机译:具有广义假设和应用的离散时间队列中的随机分解

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摘要

For several specific queueing models with a vacation policy, the stationary system occupancy at the beginning of a rantdom slot is distributed as the sum of two independent random variables. One of these variables is the stationary number of customers in an equivalent queueing system with no vacations. For models in continuous time with Poissonian arrivals, this result is well-known, and referred to as stochastic decomposition, with proof provided by Fuhrmann and Cooper. For models in discrete time, this result received less attention, with no proof available to date. In this paper, we first establish a proof of the decomposition result in discrete time. When compared to the proof in continuous time, conditions for the proof in discrete time are somewhat more general. Second, we explore four different examples: non-preemptive proirity systems, slot-bound priority systems, polling systems, and fiber delay line (FDL) buffer systems. The first two examples are known results from literature that are given here as an illustration. The third is a new example, and the last one (FDL buffer systems) shows new results. It is shown that in some cases the queueing analysis can be considerably simplified using this property.
机译:对于具有休假策略的几个特定排队模型,在备用时隙开始时的固定系统占用率将作为两个独立随机变量之和分配。这些变量之一是在没有休假的等效排队系统中的固定客户数量。对于具有Poissonian到达的连续时间模型,此结果是众所周知的,并称为随机分解,由Fuhrmann和Cooper提供证明。对于离散时间的模型,此结果受到的关注较少,迄今为止尚无可用的证据。在本文中,我们首先建立了离散时间分解结果的证明。与连续时间的证明相比,离散时间的证明条件更为普遍。其次,我们探讨了四个不同的示例:非抢先式优先系统,时隙限制优先级系统,轮询系统和光纤延迟线(FDL)缓冲系统。前两个示例是文献中的已知结果,在此作为示例给出。第三个是一个新示例,最后一个(FDL缓冲系统)显示了新结果。结果表明,在某些情况下,使用此属性可以大大简化排队分析。

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