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An Importance Sampling Approach to the Estimation of Algorithm Performance in Automated Algorithm Design Read chapter Read first chapter

2017 | OriginalPaper | Chapter

An Approximation Algorithm for Preemptive Speed Scaling Scheduling of Parallel Jobs with Migration

Authors : Alexander Kononov, Yulia Kovalenko

Published in: Learning and Intelligent Optimization

Publisher: Springer International Publishing

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Abstract

In this paper we consider a problem of preemptive scheduling rigid parallel jobs on speed scalable processors. Each job is specified by its release date, its deadline, its processing volume and the number of processors, which are required for execution of the job. We propose a new strongly polynomial approximation algorithm for the energy minimization problem with migration of jobs.

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Metadata
Title
An Approximation Algorithm for Preemptive Speed Scaling Scheduling of Parallel Jobs with Migration
Authors
Alexander Kononov
Yulia Kovalenko
Copyright Year
2017
Book
Learning and Intelligent Optimization

Print ISBN: 978-3-319-69403-0

Electronic ISBN: 978-3-319-69404-7

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-69404-7_30

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