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

doi:10.1007/s10479-008-0312-7

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

2008-02-02

8

PRE

AI

Anand Sivasubramaniam

N

Natarajan Gautam

DOI：10.1007/s10479-008-0312-7

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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.

Keywords:

quasi-birth-death processes

matrix-analytic methods

stochastic decomposition

parallel-server fork-join queues

stochastic networks

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

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