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HEAVY-TRAFFIC ANALYSIS OF A NON-PREEMPTIVE MULTI-CLASS QUEUE WITH RELATIVE PRIORITIES

Published online by Cambridge University Press:  20 January 2015

A. Izagirre
Affiliation:
CNRS; IRIT; 2 rue C. Camichel, F-31071 Toulouse, France CNRS; LAAS; 7 avenue du colonel Roche, F-31400 Toulouse, France Université de Toulouse;INP, INSA; IRIT, LAAS; F-31400 Toulouse, France E-mail: ane.izagirre@laas.fr, urtzi@laas.fr, maaike.verloop@enseeiht.fr
I.M. Verloop
Affiliation:
CNRS; IRIT; 2 rue C. Camichel, F-31071 Toulouse, France Université de Toulouse;INP, INSA; IRIT, LAAS; F-31400 Toulouse, France E-mail: ane.izagirre@laas.fr, urtzi@laas.fr, maaike.verloop@enseeiht.fr
U. Ayesta
Affiliation:
CNRS; LAAS; 7 avenue du colonel Roche, F-31400 Toulouse, France IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain UPV/EHU, University of the Basque Country, 20018 Donostia, Spain Université de Toulouse;INP, INSA; IRIT, LAAS; F-31400 Toulouse, France E-mail: ane.izagirre@laas.fr, urtzi@laas.fr, maaike.verloop@enseeiht.fr
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Abstract

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We study the steady-state queue-length vector in a multi-class queue with relative priorities. Upon service completion, the probability that the next served customer is from class k is controlled by class-dependent weights. Once a customer has started service, it is served without interruption until completion. We establish a state-space collapse for the scaled queue-length vector in the heavy-traffic regime, that is, in the limit the scaled queue-length vector is distributed as the product of an exponentially distributed random variable and a deterministic vector. We observe that the scaled queue length reduces as classes with smaller mean service requirement obtain relatively larger weights. We finally show that the scaled waiting time of a class-k customer is distributed as the product of two exponentially distributed random variables.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2015 

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