Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing

Detalhes bibliográficos
Autor(a) principal: Silva, Wellington Francisco da [UNESP]
Data de Publicação: 2020
Outros Autores: Spolon, Roberta [UNESP], Lobato, Renata Spolon [UNESP], Manacero Junior, Aleardo [UNESP], Cavenaghi Humber, Marcos Antonio, Rocha, A., Perez, B. E., Penalvo, F. G., Miras, M. D., Goncalves, R.
Tipo de documento: Artigo de conferência
Idioma: por
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/209985
Resumo: The computational demand of recent years has made a new computational paradigm become extremely necessary to meet the demand for resources. Cloud computing has been widely used and is a reality in all sectors that demand computational use allied with security and with ease of management. Gigantic data centers were created to meet ever-increasing demand. Processing, memory and storage are delivered to end customers who do not have the energy, cooling, hardware, software, licensing and management concerns, paying only for what they really need. Considering that the user requests resources to perform a certain task, it is necessary to create efficient mechanisms of allocation of resources and fair collection metrics. In this work a review is made of concepts of cloud computing and resource scheduling and analyze two scheduling algorithms that use particle swarm. Finally, the particle swarm algorithm is implemented to make analysis of the best parameter configuration to meet the demand for virtual machineallocation in cloud computing. The amount of CPU, memory and disk is considered for calculation.
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spelling Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud ComputingCloud computingvirtualizationscheduling of resourcesThe computational demand of recent years has made a new computational paradigm become extremely necessary to meet the demand for resources. Cloud computing has been widely used and is a reality in all sectors that demand computational use allied with security and with ease of management. Gigantic data centers were created to meet ever-increasing demand. Processing, memory and storage are delivered to end customers who do not have the energy, cooling, hardware, software, licensing and management concerns, paying only for what they really need. Considering that the user requests resources to perform a certain task, it is necessary to create efficient mechanisms of allocation of resources and fair collection metrics. In this work a review is made of concepts of cloud computing and resource scheduling and analyze two scheduling algorithms that use particle swarm. Finally, the particle swarm algorithm is implemented to make analysis of the best parameter configuration to meet the demand for virtual machineallocation in cloud computing. The amount of CPU, memory and disk is considered for calculation.Univ Estadual Paulista Julio de Mesquita Filho Ba, Fac Ciencias, Bauru, SP, BrazilUniv Estadual Paulista Julio de Mesquita Filho Ba, Dept Comp, Fac Ciencias, Bauru, SP, BrazilUniv Estadual Paulista Julio de Mesquita Filho Sa, Dept Ciencias Comp & Estat, Sao Jose Do Rio Preto, SP, BrazilFac Business Toronto, Inst Technol & Adv Learning Colonel Samuel Smith, Pk Dr, Toronto, ON, CanadaUniv Estadual Paulista Julio de Mesquita Filho Ba, Fac Ciencias, Bauru, SP, BrazilUniv Estadual Paulista Julio de Mesquita Filho Ba, Dept Comp, Fac Ciencias, Bauru, SP, BrazilUniv Estadual Paulista Julio de Mesquita Filho Sa, Dept Ciencias Comp & Estat, Sao Jose Do Rio Preto, SP, BrazilIeeeUniversidade Estadual Paulista (Unesp)Fac Business TorontoSilva, Wellington Francisco da [UNESP]Spolon, Roberta [UNESP]Lobato, Renata Spolon [UNESP]Manacero Junior, Aleardo [UNESP]Cavenaghi Humber, Marcos AntonioRocha, A.Perez, B. E.Penalvo, F. G.Miras, M. D.Goncalves, R.2021-06-25T12:35:51Z2021-06-25T12:35:51Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject62020 15th Iberian Conference On Information Systems And Technologies (cisti'2020). New York: Ieee, 6 p., 2020.2166-0727http://hdl.handle.net/11449/209985WOS:000612720600220Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPpor2020 15th Iberian Conference On Information Systems And Technologies (cisti'2020)info:eu-repo/semantics/openAccess2021-10-23T19:50:12Zoai:repositorio.unesp.br:11449/209985Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T19:50:12Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing
title Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing
spellingShingle Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing
Silva, Wellington Francisco da [UNESP]
Cloud computing
virtualization
scheduling of resources
title_short Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing
title_full Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing
title_fullStr Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing
title_full_unstemmed Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing
title_sort Particle Swarm Algorithm Parameters Analysis for Scheduling Virtual Machines in Cloud Computing
author Silva, Wellington Francisco da [UNESP]
author_facet Silva, Wellington Francisco da [UNESP]
Spolon, Roberta [UNESP]
Lobato, Renata Spolon [UNESP]
Manacero Junior, Aleardo [UNESP]
Cavenaghi Humber, Marcos Antonio
Rocha, A.
Perez, B. E.
Penalvo, F. G.
Miras, M. D.
Goncalves, R.
author_role author
author2 Spolon, Roberta [UNESP]
Lobato, Renata Spolon [UNESP]
Manacero Junior, Aleardo [UNESP]
Cavenaghi Humber, Marcos Antonio
Rocha, A.
Perez, B. E.
Penalvo, F. G.
Miras, M. D.
Goncalves, R.
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Fac Business Toronto
dc.contributor.author.fl_str_mv Silva, Wellington Francisco da [UNESP]
Spolon, Roberta [UNESP]
Lobato, Renata Spolon [UNESP]
Manacero Junior, Aleardo [UNESP]
Cavenaghi Humber, Marcos Antonio
Rocha, A.
Perez, B. E.
Penalvo, F. G.
Miras, M. D.
Goncalves, R.
dc.subject.por.fl_str_mv Cloud computing
virtualization
scheduling of resources
topic Cloud computing
virtualization
scheduling of resources
description The computational demand of recent years has made a new computational paradigm become extremely necessary to meet the demand for resources. Cloud computing has been widely used and is a reality in all sectors that demand computational use allied with security and with ease of management. Gigantic data centers were created to meet ever-increasing demand. Processing, memory and storage are delivered to end customers who do not have the energy, cooling, hardware, software, licensing and management concerns, paying only for what they really need. Considering that the user requests resources to perform a certain task, it is necessary to create efficient mechanisms of allocation of resources and fair collection metrics. In this work a review is made of concepts of cloud computing and resource scheduling and analyze two scheduling algorithms that use particle swarm. Finally, the particle swarm algorithm is implemented to make analysis of the best parameter configuration to meet the demand for virtual machineallocation in cloud computing. The amount of CPU, memory and disk is considered for calculation.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
2021-06-25T12:35:51Z
2021-06-25T12:35:51Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv 2020 15th Iberian Conference On Information Systems And Technologies (cisti'2020). New York: Ieee, 6 p., 2020.
2166-0727
http://hdl.handle.net/11449/209985
WOS:000612720600220
identifier_str_mv 2020 15th Iberian Conference On Information Systems And Technologies (cisti'2020). New York: Ieee, 6 p., 2020.
2166-0727
WOS:000612720600220
url http://hdl.handle.net/11449/209985
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv 2020 15th Iberian Conference On Information Systems And Technologies (cisti'2020)
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 6
dc.publisher.none.fl_str_mv Ieee
publisher.none.fl_str_mv Ieee
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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