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Marginal queue length approximations for a two-layered network with correlated queues

机译:具有两层网络的边际队列长度近似值   相关队列

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摘要

We consider an extension of the classical machine-repair model, where weassume that the machines, apart from receiving service from the repairman, alsoserve queues of products. The extended model can be viewed as a layeredqueueing network, where the first layer consists of the queues of products andthe second layer is the ordinary machine-repair model. Since the repair time ofone machine may affect the time the other machine is not able to processproducts, the downtimes of the machines are correlated. This correlation leadsto dependence between the queues of products in the first layer. Analysis ofthese queue length distributions is hard, since the exact dependence structurefor the downtimes, or the queue lengths, is not known. Therefore, we obtain anapproximation for the complete marginal queue length distribution of any queuein the first layer, by viewing such a queue as a single server queue withcorrelated server downtimes. Under an explicit assumption on the form of thedowntime dependence, we obtain exact results for the queue length distributionfor that single server queue. We use these exact results to approximate themachine-repair model. We do so by computing the downtime correlation for thelatter model and by subsequently using this information to fine-tune theparameters we introduced to the single server queue. As a result, weimmediately obtain an approximation for the queue length distributions ofproducts in the machine-repair model, which we show to be highly accurate byextensive numerical experiments.
机译:我们考虑了经典机器维修模型的扩展,在该模型中,我们假定机器除了从修理人员那里得到服务之外,还可以提供产品队列。扩展模型可以看作是分层排队网络,其中第一层由产品队列组成,第二层是普通的机器维修模型。由于一台机器的维修时间可能会影响另一台机器无法处理产品的时间,因此需要对两台机器的停机时间进行关联。这种相关性导致第一层产品队列之间的依赖性。由于不知道停机时间或队列长度的确切依存关系,因此很难对这些队列长度分布进行分析。因此,通过将这样的队列视为与服务器停机时间相关的单个服务器队列,我们​​可以获得第一层中任何队列的完整边际队列长度分布的近似值。在对停机时间依赖性形式的明确假设下,我们获得了该单个服务器队列的队列长度分布的精确结果。我们使用这些精确的结果来近似机器维修模型。为此,我们为后一种模型计算了停机时间的相关性,然后通过使用此信息来微调引入单个服务器队列的参数。结果,我们立即获得了机器维修模型中产品的队列长度分布的近似值,通过大量的数值实验表明该算法是高度准确的。

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