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Partitioning of Servers in Queueing Systems During Rush Hour

机译:在高峰时段对排队系统中的服务器进行分区

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摘要

This paper is motivated by two phenomena observed in many queueing systems in practice. The first is the partitioning of server capacity among different customers based on their service time requirements. The second is rush hour demand where a large number of customers arrive over a short period of time followed by few or no arrivals for an extended period thereafter. We study a system with multiple parallel servers and multiple customer classes. The servers can be partitioned into server groups, each dedicated to a single customer class. The system operates under a rush hour regime with a large number of customers arriving at the beginning of the rush hour period. We show that this allows us to reduce the problem to one that is deterministic and for which closed-form solutions can be obtained. We compare the performance of the system with and without server partitioning during rush hour and address three basic questions. (1) Is partitioning beneficial to the system? (2) Is it equally beneficial to all customer classes? (3) If it is implemented, what is an optimal partition? We evaluate the applicability of our results to systems where customers arrive over time using (1) deterministic fluid models and (2) simulation models for systems with stochastic interarrival times.
机译:本文的动机是在实践中在许多排队系统中观察到的两种现象。首先是根据不同客户的服务时间要求在服务器容量之间进行划分。第二个是高峰时段需求,大量客户在短时间内到达,然后在很长一段时间内很少或根本没有到达。我们研究了具有多个并行服务器和多个客户类别的系统。可以将服务器划分为服务器组,每个服务器组专用于一个客户类别。该系统在高峰时段制度下运行,大量客户在高峰时段开始时到达。我们表明,这使我们可以将问题简化为确定性的问题,并且可以针对该问题获得封闭形式的解决方案。我们比较高峰时段有无服务器分区的系统性能,并回答了三个基本问题。 (1)分区对系统有益吗? (2)是否对所有客户类别都同样有利? (3)如果实现,最佳分区是什么?我们使用(1)确定性流体模型和(2)具有随机到达时间的系统的仿真模型来评估结果对客户随时间到达的系统的适用性。

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