Heavy-traffic extreme-value limits for queues

Glynn, Peter W.; Whitt, Ward

We consider the maximum waiting time among the first n customers in the GI/G/1 queue. We use strong approximations to prove, under regularity conditions, convergence of the normalized maximum wait to the Gumbel extreme-value distribution when the traffic intensity ρ approaches 1 from below and n approaches infinity at a suitable rate. The normalization depends on the interarrival-time and service-time distributions only through their first two moments, corresponding to the iterated limit in which first ρ approaches 1 and then n approaches infinity. We need n to approach infinity sufficiently fast so that n ( 1 − ρ )2 → ∞. We also need n to approach infinity sufficiently slowly: If the service time has a pth moment for ρ > 2, then it suffices for ( 1 − ρ ) n 1 / p to remain bounded; if the service time has a finite moment generating function, then it suffices to have ( 1 − ρ ) log n → 0. This limit can hold even when the normalized maximum waiting time fails to converge to the Gumbel distribution as n → ∞ for each fixed ρ. Similar limits hold for the queue length process.


Also Published In

Operations Research Letters

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Academic Units
Industrial Engineering and Operations Research
Published Here
September 19, 2017