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A queueing model with independent arrivals, and its fluid and diffusion limits

机译:具有独立到达的排队模型及其流体和扩散极限

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摘要

We study a queueing model with ordered arrivals, which can be called the Δ_((i))/GI/1 queue. Here, customers from a fixed, finite, population independently sample a time to arrive from some given distribution F, and enter the queue in order of the sampled arrival times. Thus, the arrival times are order statistics, and the inter-arrival times are differences of consecutive order statistics. They are served by a single server with independent and identically distributed service times, with general service distribution G. The discrete event model is analytically intractable. Thus, we develop fluid and diffusion limits for the performance metrics of the queue. The fluid limit of the queue length is observed to be a reflection of a 'fluid netput' process, while the diffusion limit is observed to be a function of a Brownian motion and a Brownian bridge process or 'diffusion netput' process. The diffusion limit can be seen as being reflected through the directional derivative of the Skorokhod regulator of the fluid netput process in the direction of the diffusion netput process. We also observe what may be interpreted as a sample path Little's Law. Sample path analysis reveals various operating regimes where the diffusion limit switches between a free diffusion, a reflected diffusion process, and the zero process, with possible discontinuities during regime switches. The weak convergence results are established in the M_1 topology.
机译:我们研究了有序到达的排队模型,可以将其称为Δ_((i))/ GI / 1队列。在这里,来自固定,有限人口的客户独立地采样从某个给定分布F到达的时间,并按采样到达时间的顺序进入队列。因此,到达时间是订单统计,到达间隔时间是连续订单统计的差。它们由具有独立且均等分布的服务时间的单一服务器提供服务,并具有一般的服务分配G。离散事件模型在分析上很棘手。因此,我们为队列的性能指标制定了流动和扩散限制。观察到队列长度的流体极限是“流体净输出”过程的反映,而观察到的扩散极限是布朗运动和布朗桥过程或“扩散净输出”过程的函数。扩散极限可以看作是通过流体净积过程的Skorokhod调节器的方向导数在扩散净积过程的方向反映出来的。我们还观察到可能被解释为利特尔定律的样本路径。样本路径分析揭示了各种运行状态,其中扩散极限在自由扩散,反射扩散过程和零过程之间切换,在状态切换期间可能会出现间断。在M_1拓扑中建立了弱收敛结果。

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