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Economies of scale in queues with sources having power-law large deviation scalings

Part of: Limit theorems Stochastic processes Special processes

Published online by Cambridge University Press:  14 July 2016

N. G. Duffield
N. G. Duffield*
Affiliation:
AT&T Laboratories
*
∗ Postal address: AT&T Laboratories, Room 2D-113, 600 Mountain Avenue, Murray Hill, NJ 07974, USA.
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Abstract

We analyse the queue QL at a multiplexer with L sources which may display long-range dependence. This includes, for example, sources modelled by fractional Brownian motion (FBM). The workload processes W due to each source are assumed to have large deviation properties of the form P[W t/a(t) > x] ≈ exp[– v(t)K(x)] for appropriate scaling functions a and v, and rate-function K. Under very general conditions limL→x L –1 log P[QL > Lb] = – I(b), provided the offered load is held constant, where the shape function I is expressed in terms of the cumulant generating functions of the input traffic. For power-law scalings v(t) = tv, a(t) = ta (such as occur in FBM) we analyse the asymptotics of the shape function limb→x b –u/a (I(b) – δbv/a ) = vu for some exponent u and constant v depending on the sources. This demonstrates the economies of scale available though the multiplexing of a large number of such sources, by comparison with a simple approximation P[QL > Lb] ≈ exp[−δLbv/a ] based on the asymptotic decay rate δ alone. We apply this formula to Gaussian processes, in particular FBM, both alone, and also perturbed by an Ornstein–Uhlenbeck process. This demonstrates a richer potential structure than occurs for sources with linear large deviation scalings.

Keywords

LARGE DEVIATIONSSCALING LIMITSATM MULTIPLEXERSFRACTIONAL BROWNIAN MOTIONEFFECTIVE BANDWIDTH APPROXIMATION

MSC classification

Primary: 60K25: Queueing theory
Secondary: 60F10: Large deviations 60G18: Self-similar processes

Information

Type
Research Papers
Information
Journal of Applied Probability , Volume 33 , Issue 3 , September 1996 , pp. 840 - 857
Copyright
Copyright © Applied Probability Trust 1996 

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