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A diffusion approximation for correlation in queues

Published online by Cambridge University Press:  14 July 2016

C. M. Woodside*
Affiliation:
Carleton University
B. Pagurek*
Affiliation:
Carleton University
G. F. Newell*
Affiliation:
University of California
*
Postal address: Department of Systems Engineering and Computing Science, Carleton University, Ottawa, Canada K1S 5B6.
Postal address: Department of Systems Engineering and Computing Science, Carleton University, Ottawa, Canada K1S 5B6.
∗∗Postal address: Department of Civil Engineering, University of California, Berkeley, CA 94720, U.S.A.

Abstract

A diffusion model is used to find heavy traffic approximate autocorrelation functions for several variables in queueing systems (i.e. for waiting time, system time, number in system and unfinished work). A table is given by which correlations can easily be found for each variable in any GI/G/1 queue. Further, the infinite sum or integral of the autocorrelations is also found, and the spectral density function. The sum has applications in statistical analysis of queues.

Extensive comparisons of approximate and exact correlations and their sums are reported, particularly for waiting times and system times, but also including number in system in M/M/1 queues. In general the correlations have similar accuracy to the probability distributions found by diffusion approximations. The percentage error is less for number in system than for waiting time.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 

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