z-logo
open-access-imgOpen Access
Optimal Control of a Multiclass, Flexible Queueing System
Author(s) -
Noah Gans,
Garrett J. van Ryzin
Publication year - 1997
Publication title -
operations research
Language(s) - English
Resource type - Journals
eISSN - 1526-5463
pISSN - 0030-364X
DOI - 10.1287/opre.45.5.677
Subject(s) - heuristics , computer science , queueing theory , mathematical optimization , set (abstract data type) , service (business) , job shop , process (computing) , admission control , class (philosophy) , distributed computing , operations research , job shop scheduling , flow shop scheduling , mathematics , computer network , quality of service , routing (electronic design automation) , economy , economics , programming language , operating system , artificial intelligence
We consider a general class of queueing systems with multiple job types and a flexible service facility. The arrival times and sizes of incoming jobs are random, and correlations among the sizes of arriving job types are allowed. By choosing among a finite set of configurations, the facility can dynamically control the rates at which it serves the various job types. We define system work at any given time as the minimum time required to process all jobs currently in the backlog. This quantity is determined by solving a linear program defined by the set of processing configurations. The problem we study is how to dynamically choose configurations to minimize the time average system work. Using bounds and heuristics, we analyze a class of service policies that is provably asymptotically optimal as system utilization approaches one, as well as a policy that in numerical studies performs near-optimally in moderate traffic. Our analysis also yields a closed-form expression for the optimal, average work in heav...

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom