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Simple Near-Optimal Scheduling for the M/G/1

Authors:

Ziv Scully,

Mor Harchol-Balter,

Alan Scheller-WolfAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 47, Issue 2

Pages 24 - 26

https://doi.org/10.1145/3374888.3374898

Published: 04 December 2019 Publication History

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Abstract

We consider the problem of preemptively scheduling jobs to minimize mean response time of an M/G/1 queue. When the scheduler knows each job's size, the shortest remaining processing time (SRPT) policy is optimal. Unfortunately, in many settings we do not have access to each job's size. Instead, we know only the job size distribution. In this setting, the Gittins policy is known to minimize mean response time, but its complex priority structure can be computationally intractable. A much simpler alternative to Gittins is the shortest expected remaining processing time (SERPT) policy. While SERPT is a natural extension of SRPT to unknown job sizes, it is unknown how close SERPT is to optimal.

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Cited By

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Li ZHu PHuang L(2024)Offline Learning-Based Multi-User Delay-Constrained Scheduling2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS)10.1109/MASS62177.2024.00023(92-99)Online publication date: 23-Sep-2024
https://doi.org/10.1109/MASS62177.2024.00023
Hu PPan LChen YFang ZHuang LChong SJoo CLee K(2022)Effective multi-user delay-constrained scheduling with deep recurrent reinforcement learningProceedings of the Twenty-Third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing10.1145/3492866.3549712(1-10)Online publication date: 3-Oct-2022
https://dl.acm.org/doi/10.1145/3492866.3549712

Simple Near-Optimal Scheduling for the M/G/1

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Simple Near-Optimal Scheduling for the M/G/1
SIGMETRICS

We consider the problem of preemptively scheduling jobs to minimize mean response time of an M/G/1 queue. When we know each job's size, the shortest remaining processing time (SRPT) policy is optimal. Unfortunately, in many settings we do not have access ...
Simple Near-Optimal Scheduling for the M/G/1
SIGMETRICS '20: Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems

We consider the problem of preemptively scheduling jobs to minimize mean response time of an M/G/1 queue. When we know each job's size, the shortest remaining processing time (SRPT) policy is optimal. Unfortunately, in many settings we do not have ...
Simple Near-Optimal Scheduling for the M/G/1

We consider the problem of preemptively scheduling jobs to minimize mean response time of an M/G/1 queue. When we know each job's size, the shortest remaining processing time (SRPT) policy is optimal. Unfortunately, in many settings we do not have ...

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cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 47, Issue 2

September 2019

37 pages

ISSN:0163-5999

DOI:10.1145/3374888

Editor:
Zhenhua Liu
Stony Brook University

Issue’s Table of Contents

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 04 December 2019

Published in SIGMETRICS Volume 47, Issue 2

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Li ZHu PHuang L(2024)Offline Learning-Based Multi-User Delay-Constrained Scheduling2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS)10.1109/MASS62177.2024.00023(92-99)Online publication date: 23-Sep-2024
https://doi.org/10.1109/MASS62177.2024.00023
Hu PPan LChen YFang ZHuang LChong SJoo CLee K(2022)Effective multi-user delay-constrained scheduling with deep recurrent reinforcement learningProceedings of the Twenty-Third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing10.1145/3492866.3549712(1-10)Online publication date: 3-Oct-2022
https://dl.acm.org/doi/10.1145/3492866.3549712

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