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Asymptotic expansions for the sojourn time distribution in the M/G/1-PS queue

机译:M / G / 1-PS队列中停留时间分布的渐近展开

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We consider the M/G/1 queue with a processor sharing server. We study the conditional sojourn time distribution, conditioned on the customer's service requirement, as well as the unconditional distribution, in various asymptotic limits. These include large time and/or large service request, and heavy traffic, where the arrival rate is only slightly less than the service rate. Our results demonstrate the possible tail behaviors of the unconditional distribution, which was previously known in the cases G = M and G = D (where it is purely exponential). We assume that the service density decays at least exponentially fast. We use various methods for the asymptotic expansion of integrals, such as the Laplace and saddle point methods.
机译:我们考虑带有处理器共享服务器的M / G / 1队列。我们研究了在各种渐近极限条件下的有条件的逗留时间分布,这些条件取决于客户的服务需求以及无条件的分布。这些包括大量的时间和/或大量的服务请求,以及繁忙的交通,到达率仅略低于服务率。我们的结果证明了无条件分布的可能的尾部行为,这以前在情况G = M和G = D(纯指数)的情况下是已知的。我们假设服务密度至少以指数方式快速衰减。我们使用各种方法进行积分的渐近展开,例如Laplace和鞍点方法。

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