重流量单服务器队列及其转换方法

Pub Date : 2023-09-01 DOI:10.1016/j.indag.2023.02.004
M.A.A. Boon , A.J.E.M. Janssen , J.S.H. van Leeuwaarden
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引用次数: 0

摘要

大流量限制理论关注的是接近临界运行且面临严重排队时间的队列。令W表示GI/G/1队列的稳态等待时间。Kingman(1961)表明,当适当缩放W时,当系统负荷接近1时,W在分布上收敛于指数随机变量。这个著名结果的原始证明使用了变换方法。从W的pdf的拉普拉斯变换(Pollaczek的轮廓积分表示)开始,Kingman证明了变换的收敛性,因此所涉及的随机变量是弱收敛的。应用并扩展了该变换方法,得到了具有误差评估的矩的收敛性。我们还演示了如何将变换方法应用于kingman型和高斯高流量状态下的所谓近确定性队列。我们用数值方法证明了各种繁忙交通近似的准确性。
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Heavy-traffic single-server queues and the transform method

Heavy-traffic limit theory is concerned with queues that operate close to criticality and face severe queueing times. Let W denote the steady-state waiting time in the GI/G/1 queue. Kingman (1961) showed that W, when appropriately scaled, converges in distribution to an exponential random variable as the system’s load approaches 1. The original proof of this famous result uses the transform method. Starting from the Laplace transform of the pdf of W (Pollaczek’s contour integral representation), Kingman showed convergence of transforms and hence weak convergence of the involved random variables. We apply and extend this transform method to obtain convergence of moments with error assessment. We also demonstrate how the transform method can be applied to so-called nearly deterministic queues in a Kingman-type and a Gaussian heavy-traffic regime. We demonstrate numerically the accuracy of the various heavy-traffic approximations.

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