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Sharp and simple bounds for the Erlang delay and loss formulae

机译:Erlang延迟和损失公式的界限简单明了

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We prove some simple and sharp lower and upper bounds for the Erlang delay and loss formulae and for the number of servers that invert the Erlang delay and loss formulae. We also suggest simple and sharp approximations for the number of servers that invert the Erlang delay and loss formulae. We illustrate the importance of these bounds by using them to establish convexity proofs. We show that the probability that the M/M/s queue is empty is a decreasing and convex function of the traffic intensity. We also give a very short proof to show that the Erlang delay formula is convex in the traffic intensity when the number of servers is held constant. The complete proof of this classical result has never been published. We also give a very short proof to show that the Erlang delay formula is a convex function of the (positive integer) number of servers. One of our results is then used to get a sharp bound to the Flow Assignment Problem.
机译:我们证明了Erlang延迟和损失公式以及反转Erlang延迟和损失公式的服务器数量的一些简单而明确的下界和上限。我们还建议对反转Erlang延迟和损耗公式的服务器数量进行简单而清晰的估计。我们通过使用它们来建立凸性证明来说明这些边界的重要性。我们表明,M / M / s队列为空的概率是交通强度的递减函数。我们还给出了一个非常简短的证明,以证明当服务器数量保持恒定时,Erlang延迟公式在流量强度上是凸的。这种经典结果的完整证据尚未公布。我们还给出了一个非常简短的证明,以证明Erlang延迟公式是服务器(正整数)数量的凸函数。然后,我们的结果之一将用于明确分配流程分配问题。

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