Hybrid algorithms for independent batch scheduling in grids

Grid computing has emerged as a wide area distributed paradigm for solving large-scale problems in science, engineering, etc. and is known as the family of eScience grid-enabled applications. Computing planning of incoming jobs efficiently with available machines in the grid system is the main requi...

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Detalles Bibliográficos
Autores: Xhafa Xhafa, Fatos|||0000-0001-6569-5497, Kolodziej, Joanna, Barolli, Leonard, Kolici, Vladi, Miho, Rozeta, Takizawa, Makoto
Tipo de recurso: artículo
Fecha de publicación:2012
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/127858
Acceso en línea:https://hdl.handle.net/2117/127858
https://dx.doi.org/10.1504/IJWGS.2012.048402
Access Level:acceso abierto
Palabra clave:Computational grids (Computer systems)
Genetic algorithms
Fl owtime
GAs
Hierarchic optimisation
Hybridisation
Makespan
Meta-heuristics
Simultaneous optimisation
Tabu search
TS
Computació distribuïda
Algorismes genètics
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
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spelling Hybrid algorithms for independent batch scheduling in gridsXhafa Xhafa, Fatos|||0000-0001-6569-5497Kolodziej, JoannaBarolli, LeonardKolici, VladiMiho, RozetaTakizawa, MakotoComputational grids (Computer systems)Genetic algorithmsFl owtimeGAsHierarchic optimisationHybridisationMakespanMeta-heuristicsSimultaneous optimisationTabu searchTSComputació distribuïdaAlgorismes genèticsÀrees temàtiques de la UPC::Informàtica::Informàtica teòricaGrid computing has emerged as a wide area distributed paradigm for solving large-scale problems in science, engineering, etc. and is known as the family of eScience grid-enabled applications. Computing planning of incoming jobs efficiently with available machines in the grid system is the main requirement for optimised system performance. One version of the problem is that of independent batch scheduling, in which jobs are assumed to be independent and are scheduled in batches aimed at minimising the makespan and flowtime. Given the hardness of the problem, heuristics are used to find high quality solutions for practical purposes of designing efficient grid schedulers. Recently, considerable efforts were spent in implementing and evaluating not only stand-alone heuristics and meta-heuristics, but also their hybridisation into even higher level algorithms. In this paper, we present a study on the performance of two popular algorithms for the problem, namely Genetic Algorithms (GAs) and Tabu Search (TS) and two hybridisations involving them, namely, the GA (TS) and GA-TS, which differ in the way the main control and cooperation among GA and TS are implemented. The hierarchic and simultaneous optimisation modes are considered for the bi-objective scheduling problem. Evaluation is done using different grid scenarios generated by a grid simulator. The computational results showed that the hybrid algorithm outperforms both the GA and TS for the makespan parameter, but not for the flowtime parameter.Peer Reviewed20122012-01-0120192019-01-30journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/127858https://dx.doi.org/10.1504/IJWGS.2012.048402reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1278582026-05-27T15:37:01Z
dc.title.none.fl_str_mv Hybrid algorithms for independent batch scheduling in grids
title Hybrid algorithms for independent batch scheduling in grids
spellingShingle Hybrid algorithms for independent batch scheduling in grids
Xhafa Xhafa, Fatos|||0000-0001-6569-5497
Computational grids (Computer systems)
Genetic algorithms
Fl owtime
GAs
Hierarchic optimisation
Hybridisation
Makespan
Meta-heuristics
Simultaneous optimisation
Tabu search
TS
Computació distribuïda
Algorismes genètics
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
title_short Hybrid algorithms for independent batch scheduling in grids
title_full Hybrid algorithms for independent batch scheduling in grids
title_fullStr Hybrid algorithms for independent batch scheduling in grids
title_full_unstemmed Hybrid algorithms for independent batch scheduling in grids
title_sort Hybrid algorithms for independent batch scheduling in grids
dc.creator.none.fl_str_mv Xhafa Xhafa, Fatos|||0000-0001-6569-5497
Kolodziej, Joanna
Barolli, Leonard
Kolici, Vladi
Miho, Rozeta
Takizawa, Makoto
author Xhafa Xhafa, Fatos|||0000-0001-6569-5497
author_facet Xhafa Xhafa, Fatos|||0000-0001-6569-5497
Kolodziej, Joanna
Barolli, Leonard
Kolici, Vladi
Miho, Rozeta
Takizawa, Makoto
author_role author
author2 Kolodziej, Joanna
Barolli, Leonard
Kolici, Vladi
Miho, Rozeta
Takizawa, Makoto
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Computational grids (Computer systems)
Genetic algorithms
Fl owtime
GAs
Hierarchic optimisation
Hybridisation
Makespan
Meta-heuristics
Simultaneous optimisation
Tabu search
TS
Computació distribuïda
Algorismes genètics
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
topic Computational grids (Computer systems)
Genetic algorithms
Fl owtime
GAs
Hierarchic optimisation
Hybridisation
Makespan
Meta-heuristics
Simultaneous optimisation
Tabu search
TS
Computació distribuïda
Algorismes genètics
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
description Grid computing has emerged as a wide area distributed paradigm for solving large-scale problems in science, engineering, etc. and is known as the family of eScience grid-enabled applications. Computing planning of incoming jobs efficiently with available machines in the grid system is the main requirement for optimised system performance. One version of the problem is that of independent batch scheduling, in which jobs are assumed to be independent and are scheduled in batches aimed at minimising the makespan and flowtime. Given the hardness of the problem, heuristics are used to find high quality solutions for practical purposes of designing efficient grid schedulers. Recently, considerable efforts were spent in implementing and evaluating not only stand-alone heuristics and meta-heuristics, but also their hybridisation into even higher level algorithms. In this paper, we present a study on the performance of two popular algorithms for the problem, namely Genetic Algorithms (GAs) and Tabu Search (TS) and two hybridisations involving them, namely, the GA (TS) and GA-TS, which differ in the way the main control and cooperation among GA and TS are implemented. The hierarchic and simultaneous optimisation modes are considered for the bi-objective scheduling problem. Evaluation is done using different grid scenarios generated by a grid simulator. The computational results showed that the hybrid algorithm outperforms both the GA and TS for the makespan parameter, but not for the flowtime parameter.
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-01-01
2019
2019-01-30
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/127858
https://dx.doi.org/10.1504/IJWGS.2012.048402
url https://hdl.handle.net/2117/127858
https://dx.doi.org/10.1504/IJWGS.2012.048402
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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