Distributed Job Scheduling based on Swarm Intelligence: A Survey

Autores
Mateos Diaz, Cristian Maximiliano; Pacini Naumovich, Elina Rocío; Garcia Garino, Carlos Gabriel
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Scientists and engineers need computational power to satisfy the increasing resource intensive nature of their simulations. For example, running Parameter Sweep Experiments (PSE) involve processing many independent jobs, given by multiple initial configurations (input parameter values) against the same program code. Hence, paradigms like Grid Computing and Cloud Computing are employed for gaining scalability. However, job scheduling in Grid and Cloud environments represents a difficult issue since it is basically NP-complete. Thus, many variants based on approximation techniques, specially those from Swarm Intelligence (SI), have been proposed. These techniques have the ability of searching for problem solutions in a very efficient way. This paper surveys SI-based job scheduling algorithms for bag-of-tasks applications(such as PSEs) on distributed computing environments, and uniformly compares them based on a derived comparison framework. We also discuss open problems and future research in the area.
Fil: Mateos Diaz, Cristian Maximiliano. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Pacini Naumovich, Elina Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Garcia Garino, Carlos Gabriel. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
Materia
Bag-Of-Tasks Applications
Grid Computing
Cloud Computing
Job Scheduling
Swarm Intelligence
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/6776
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Distributed Job Scheduling based on Swarm Intelligence: A SurveyMateos Diaz, Cristian MaximilianoPacini Naumovich, Elina RocíoGarcia Garino, Carlos GabrielBag-Of-Tasks ApplicationsGrid ComputingCloud ComputingJob SchedulingSwarm Intelligencehttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Scientists and engineers need computational power to satisfy the increasing resource intensive nature of their simulations. For example, running Parameter Sweep Experiments (PSE) involve processing many independent jobs, given by multiple initial configurations (input parameter values) against the same program code. Hence, paradigms like Grid Computing and Cloud Computing are employed for gaining scalability. However, job scheduling in Grid and Cloud environments represents a difficult issue since it is basically NP-complete. Thus, many variants based on approximation techniques, specially those from Swarm Intelligence (SI), have been proposed. These techniques have the ability of searching for problem solutions in a very efficient way. This paper surveys SI-based job scheduling algorithms for bag-of-tasks applications(such as PSEs) on distributed computing environments, and uniformly compares them based on a derived comparison framework. We also discuss open problems and future research in the area.Fil: Mateos Diaz, Cristian Maximiliano. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Pacini Naumovich, Elina Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Garcia Garino, Carlos Gabriel. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaElsevier2014-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/ziphttp://hdl.handle.net/11336/6776Mateos Diaz, Cristian Maximiliano; Pacini Naumovich, Elina Rocío; Garcia Garino, Carlos Gabriel; Distributed Job Scheduling based on Swarm Intelligence: A Survey; Elsevier; Computers & Electrical Engineering; 40; 1; 2-2014; 252-2690045-7906enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compeleceng.2013.11.023info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0045790613003054info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:07:57Zoai:ri.conicet.gov.ar:11336/6776instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:07:57.961CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Distributed Job Scheduling based on Swarm Intelligence: A Survey
title Distributed Job Scheduling based on Swarm Intelligence: A Survey
spellingShingle Distributed Job Scheduling based on Swarm Intelligence: A Survey
Mateos Diaz, Cristian Maximiliano
Bag-Of-Tasks Applications
Grid Computing
Cloud Computing
Job Scheduling
Swarm Intelligence
title_short Distributed Job Scheduling based on Swarm Intelligence: A Survey
title_full Distributed Job Scheduling based on Swarm Intelligence: A Survey
title_fullStr Distributed Job Scheduling based on Swarm Intelligence: A Survey
title_full_unstemmed Distributed Job Scheduling based on Swarm Intelligence: A Survey
title_sort Distributed Job Scheduling based on Swarm Intelligence: A Survey
dc.creator.none.fl_str_mv Mateos Diaz, Cristian Maximiliano
Pacini Naumovich, Elina Rocío
Garcia Garino, Carlos Gabriel
author Mateos Diaz, Cristian Maximiliano
author_facet Mateos Diaz, Cristian Maximiliano
Pacini Naumovich, Elina Rocío
Garcia Garino, Carlos Gabriel
author_role author
author2 Pacini Naumovich, Elina Rocío
Garcia Garino, Carlos Gabriel
author2_role author
author
dc.subject.none.fl_str_mv Bag-Of-Tasks Applications
Grid Computing
Cloud Computing
Job Scheduling
Swarm Intelligence
topic Bag-Of-Tasks Applications
Grid Computing
Cloud Computing
Job Scheduling
Swarm Intelligence
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Scientists and engineers need computational power to satisfy the increasing resource intensive nature of their simulations. For example, running Parameter Sweep Experiments (PSE) involve processing many independent jobs, given by multiple initial configurations (input parameter values) against the same program code. Hence, paradigms like Grid Computing and Cloud Computing are employed for gaining scalability. However, job scheduling in Grid and Cloud environments represents a difficult issue since it is basically NP-complete. Thus, many variants based on approximation techniques, specially those from Swarm Intelligence (SI), have been proposed. These techniques have the ability of searching for problem solutions in a very efficient way. This paper surveys SI-based job scheduling algorithms for bag-of-tasks applications(such as PSEs) on distributed computing environments, and uniformly compares them based on a derived comparison framework. We also discuss open problems and future research in the area.
Fil: Mateos Diaz, Cristian Maximiliano. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Pacini Naumovich, Elina Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Garcia Garino, Carlos Gabriel. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
description Scientists and engineers need computational power to satisfy the increasing resource intensive nature of their simulations. For example, running Parameter Sweep Experiments (PSE) involve processing many independent jobs, given by multiple initial configurations (input parameter values) against the same program code. Hence, paradigms like Grid Computing and Cloud Computing are employed for gaining scalability. However, job scheduling in Grid and Cloud environments represents a difficult issue since it is basically NP-complete. Thus, many variants based on approximation techniques, specially those from Swarm Intelligence (SI), have been proposed. These techniques have the ability of searching for problem solutions in a very efficient way. This paper surveys SI-based job scheduling algorithms for bag-of-tasks applications(such as PSEs) on distributed computing environments, and uniformly compares them based on a derived comparison framework. We also discuss open problems and future research in the area.
publishDate 2014
dc.date.none.fl_str_mv 2014-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/6776
Mateos Diaz, Cristian Maximiliano; Pacini Naumovich, Elina Rocío; Garcia Garino, Carlos Gabriel; Distributed Job Scheduling based on Swarm Intelligence: A Survey; Elsevier; Computers & Electrical Engineering; 40; 1; 2-2014; 252-269
0045-7906
url http://hdl.handle.net/11336/6776
identifier_str_mv Mateos Diaz, Cristian Maximiliano; Pacini Naumovich, Elina Rocío; Garcia Garino, Carlos Gabriel; Distributed Job Scheduling based on Swarm Intelligence: A Survey; Elsevier; Computers & Electrical Engineering; 40; 1; 2-2014; 252-269
0045-7906
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compeleceng.2013.11.023
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0045790613003054
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
application/zip
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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