Generalized parallel-server fork-join queues with dynamic task scheduling

Mark S. Squillante, Yanyong Zhang, Anand Sivasubramaniam, Natarajan Gautam

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

This paper introduces a generalization of the classical parallel-server fork-join queueing system in which arriving customers fork into multiple tasks, every task is uniquely assigned to one of the set of single-server queues, and each task consists of multiple iterations of different stages of execution, including task vacations and communication among sibling tasks. Several classes of dynamic polices are considered for scheduling multiple tasks at each of the single-server queues to maintain effective server utilization. The paper presents an exact matrix-analytic analysis of generalized parallel-server fork-join queueing systems, for small instances of the stochastic model, and presents an approximate matrix-analytic analysis and fixed-point solution, for larger instances of the model.

Original languageEnglish (US)
Pages (from-to)227-255
Number of pages29
JournalAnnals of Operations Research
Volume160
Issue number1
DOIs
StatePublished - Apr 2008

All Science Journal Classification (ASJC) codes

  • General Decision Sciences
  • Management Science and Operations Research

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