A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method

Detalhes bibliográficos
Autor(a) principal: Rahmani, Amir Masoud
Data de Publicação: 2008
Outros Autores: Ali Vahedi, Mohammad
Tipo de documento: Artigo
Idioma: eng
Título da fonte: INFOCOMP: Jornal de Ciência da Computação
Texto Completo: https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/218
Resumo: Task scheduling is essential for the suitable operation of multiprocessor systems. The aim of task scheduling is to determine an assignment of tasks to processors for shortening the length of schedules. The problem of task scheduling on multiprocessor systems is known to be NP-complete in general. Solving this problem using by conventional techniques needs reasonable amounts of time. Therefore, many heuristic techniques were introduced for solving it. This paper presents a new heuristic algorithm for task scheduling, based on evolutionary method which embeds a new fast technique named Elitism Stepping into Genetic Algorithm (GA). By comparing the proposed algorithm with an existing GA-based algorithm, it is found that the computation time of the new algorithm to find a sub-optimal schedule is decreased; however, the length of schedule or the finish time is decreased too.
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spelling A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping methodTask schedulingMultiprocessor SystemsGenetic AlgorithmElitism Stepping.Task scheduling is essential for the suitable operation of multiprocessor systems. The aim of task scheduling is to determine an assignment of tasks to processors for shortening the length of schedules. The problem of task scheduling on multiprocessor systems is known to be NP-complete in general. Solving this problem using by conventional techniques needs reasonable amounts of time. Therefore, many heuristic techniques were introduced for solving it. This paper presents a new heuristic algorithm for task scheduling, based on evolutionary method which embeds a new fast technique named Elitism Stepping into Genetic Algorithm (GA). By comparing the proposed algorithm with an existing GA-based algorithm, it is found that the computation time of the new algorithm to find a sub-optimal schedule is decreased; however, the length of schedule or the finish time is decreased too.Editora da UFLA2008-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/218INFOCOMP Journal of Computer Science; Vol. 7 No. 2 (2008): June, 2008; 58-641982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/218/203Copyright (c) 2016 INFOCOMP Journal of Computer Scienceinfo:eu-repo/semantics/openAccessRahmani, Amir MasoudAli Vahedi, Mohammad2015-06-27T23:52:42Zoai:infocomp.dcc.ufla.br:article/218Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:25.240044INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method
title A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method
spellingShingle A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method
Rahmani, Amir Masoud
Task scheduling
Multiprocessor Systems
Genetic Algorithm
Elitism Stepping.
title_short A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method
title_full A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method
title_fullStr A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method
title_full_unstemmed A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method
title_sort A novel Task Scheduling in Multiprocessor Systems with Genetic Algorithm by using Elitism stepping method
author Rahmani, Amir Masoud
author_facet Rahmani, Amir Masoud
Ali Vahedi, Mohammad
author_role author
author2 Ali Vahedi, Mohammad
author2_role author
dc.contributor.author.fl_str_mv Rahmani, Amir Masoud
Ali Vahedi, Mohammad
dc.subject.por.fl_str_mv Task scheduling
Multiprocessor Systems
Genetic Algorithm
Elitism Stepping.
topic Task scheduling
Multiprocessor Systems
Genetic Algorithm
Elitism Stepping.
description Task scheduling is essential for the suitable operation of multiprocessor systems. The aim of task scheduling is to determine an assignment of tasks to processors for shortening the length of schedules. The problem of task scheduling on multiprocessor systems is known to be NP-complete in general. Solving this problem using by conventional techniques needs reasonable amounts of time. Therefore, many heuristic techniques were introduced for solving it. This paper presents a new heuristic algorithm for task scheduling, based on evolutionary method which embeds a new fast technique named Elitism Stepping into Genetic Algorithm (GA). By comparing the proposed algorithm with an existing GA-based algorithm, it is found that the computation time of the new algorithm to find a sub-optimal schedule is decreased; however, the length of schedule or the finish time is decreased too.
publishDate 2008
dc.date.none.fl_str_mv 2008-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/218
url https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/218
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/218/203
dc.rights.driver.fl_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv INFOCOMP Journal of Computer Science; Vol. 7 No. 2 (2008): June, 2008; 58-64
1982-3363
1807-4545
reponame:INFOCOMP: Jornal de Ciência da Computação
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str INFOCOMP: Jornal de Ciência da Computação
collection INFOCOMP: Jornal de Ciência da Computação
repository.name.fl_str_mv INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv infocomp@dcc.ufla.br||apfreire@dcc.ufla.br
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