We consider a fork-join system in which a fixed amount of computational resources has to be distributed among the K tasks forming the jobs. The queueing disciplines of the fork- and join- queues are First Come First Served. At each epoch, at most K tasks are in service while the others wait in the fork-queues. We propose an algorithm with a very simple implementation that allocates the computational resources in a way that aims at minimizing the join-queue lengths, and hence at reducing the expected job service time. We study its performance in saturation and under exponential service time and provide a methodology to derive the relevant performance indices. Explicit closed-form expressions for the expected response time and join-queue length are given for the cases of jobs consisting of two, three and four tasks.

Biased processor sharing in fork-join queues

Marin, Andrea
;
Rossi, Sabina
;
Sottana, Matteo
2018-01-01

Abstract

We consider a fork-join system in which a fixed amount of computational resources has to be distributed among the K tasks forming the jobs. The queueing disciplines of the fork- and join- queues are First Come First Served. At each epoch, at most K tasks are in service while the others wait in the fork-queues. We propose an algorithm with a very simple implementation that allocates the computational resources in a way that aims at minimizing the join-queue lengths, and hence at reducing the expected job service time. We study its performance in saturation and under exponential service time and provide a methodology to derive the relevant performance indices. Explicit closed-form expressions for the expected response time and join-queue length are given for the cases of jobs consisting of two, three and four tasks.
2018
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3710571
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