Multiscale Queueing Analysis

This paper introduces a new multiscale framework for estimating the tail probability of a queue fed by an arbitrary traffic process. Using traffic statistics at a small number of time scales, our analysis extends the theoretical concept of the critical time scale and provides practical approximation...

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Bibliographic Details
Published in:IEEE/ACM transactions on networking 2006-10, Vol.14 (5), p.1005-1018
Main Authors: Ribeiro, V.J., Riedi, R.H., Baraniuk, R.G.
Format: Article
Language:English
Subjects:
Admission control
Approximation
Brownian motion
Communication system traffic control
Computer simulation
critical time scale
Delay
fractional Brownian motion
Internet
long-range dependence
marginals
multifractals
multiscale
network provisioning
Network topologies
Probability
queueing
Queueing analysis
Queues
Queuing
Statistical analysis
Statistics
Studies
Tail
Telecommunication traffic
Traffic control
Traffic engineering
Traffic flow
wavelets
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Summary:This paper introduces a new multiscale framework for estimating the tail probability of a queue fed by an arbitrary traffic process. Using traffic statistics at a small number of time scales, our analysis extends the theoretical concept of the critical time scale and provides practical approximations for the tail queue probability. These approximations are non-asymptotic; that is, they apply to any finite queue threshold. While our approach applies to any traffic process, it is particularly apt for long-range-dependent (LRD) traffic. For LRD fractional Brownian motion, we prove that a sparse exponential spacing of time scales yields optimal performance. Simulations with LRD traffic models and real Internet traces demonstrate the accuracy of the approach. Finally, simulations reveal that the marginals of traffic at multiple time scales have a strong influence on queueing that is not captured well by its global second-order correlation in non-Gaussian scenarios
ISSN:1063-6692
1558-2566
DOI:10.1109/TNET.2006.882987