DocumentCode :
1402442
Title :
The M/G/1 queue with heavy-tailed service time distribution
Author :
Boxma, Onno J. ; Cohen, J.W.
Author_Institution :
CWI, Amsterdam, Netherlands
Volume :
16
Issue :
5
fYear :
1998
fDate :
6/1/1998 12:00:00 AM
Firstpage :
749
Lastpage :
763
Abstract :
In modern teletraffic applications of queueing theory, service time distributions B(t) with a heavy tail occur, i.e., 1-B(t)~Ct-v for t→∞ with v>1. For such service time distributions, not much explicit information is available concerning the tail probabilities of the corresponding waiting time distribution W(t). In the present study, which is devoted to the M/G/1 queue, a class of heavy-tailed service time distributions is introduced that does allow a rather detailed analysis of the tail behavior of the waiting time distribution. For v=1½, an explicit expression for W(t) is derived. For rational v with 1<v<2, an asymptotic series for the tail probabilities of W(t) is derived. In addition, we present an approximation for W(t), which is based on a heavy-traffic limit theorem for the M/G/1 queue with heavy-tailed service time distribution (with infinite variance); this approximation is shown to yield excellent results for values of t which are not too small, even when the load is not heavy
Keywords :
approximation theory; probability; queueing theory; series (mathematics); statistical analysis; telecommunication traffic; M/G/1 queue; approximation; asymptotic series; explicit expression; heavy-tailed service time distribution; heavy-traffic limit theorem; infinite variance; queueing theory; tail probabilities; teletraffic applications; waiting time distribution; Area measurement; Ethernet networks; Local area networks; Probability distribution; Queueing analysis; Tail; Telecommunication traffic; Time measurement; Traffic control; Wide area networks;
fLanguage :
English
Journal_Title :
Selected Areas in Communications, IEEE Journal on
Publisher :
ieee
ISSN :
0733-8716
Type :
jour
DOI :
10.1109/49.700910
Filename :
700910
Link To Document :
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