Improving virtual machine consolidation for heterogeneous cloud computing datacenters
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/SBAC-PAD.2019.00037 http://hdl.handle.net/11449/199848 |
Resumo: | Datacenters in cloud computing systems may consist of thousands of computing nodes and communication devices, requiring virtual machine placement to optimize resources utilization. Heterogeneous environments of current datacenters have not been properly evaluated yet when the number of processing nodes and network devices is considered. This paper presents an approach to place virtual machines to minimize both the number of employed computing nodes and communication costs in heterogeneous environments. We evaluate our results against other known algorithms to show the efficiency of the proposed approach, which outperforms a state-of-the-art algorithm with a result of up to 13% better for network improvement while achieves the same number of computing nodes. |
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Improving virtual machine consolidation for heterogeneous cloud computing datacentersCloud computingHeterogeneous systemsVirtual machine placementDatacenters in cloud computing systems may consist of thousands of computing nodes and communication devices, requiring virtual machine placement to optimize resources utilization. Heterogeneous environments of current datacenters have not been properly evaluated yet when the number of processing nodes and network devices is considered. This paper presents an approach to place virtual machines to minimize both the number of employed computing nodes and communication costs in heterogeneous environments. We evaluate our results against other known algorithms to show the efficiency of the proposed approach, which outperforms a state-of-the-art algorithm with a result of up to 13% better for network improvement while achieves the same number of computing nodes.Dept. of Computer Science and Statistics São Paulo State University (UNESP) São José Do Rio PretoInstitute of Computing University of CampinasFaculty of Science São Paulo State University (UNESP)Dept. of Computer Science and Statistics São Paulo State University (UNESP) São José Do Rio PretoFaculty of Science São Paulo State University (UNESP)Universidade Estadual Paulista (Unesp)Universidade Estadual de Campinas (UNICAMP)Rodrigues, Joao Antonio Magri [UNESP]De Oliveira, Fabiola Martins C.Lobato, Renata Spolon [UNESP]Spolon, Roberta [UNESP]Manacero, Aleardo [UNESP]Borin, Edson2020-12-12T01:50:56Z2020-12-12T01:50:56Z2019-10-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject176-179http://dx.doi.org/10.1109/SBAC-PAD.2019.00037Proceedings - Symposium on Computer Architecture and High Performance Computing, v. 2019-October, p. 176-179.1550-6533http://hdl.handle.net/11449/19984810.1109/SBAC-PAD.2019.000372-s2.0-85076883130Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings - Symposium on Computer Architecture and High Performance Computinginfo:eu-repo/semantics/openAccess2021-10-23T10:11:00Zoai:repositorio.unesp.br:11449/199848Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:34:05.759894Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Improving virtual machine consolidation for heterogeneous cloud computing datacenters |
title |
Improving virtual machine consolidation for heterogeneous cloud computing datacenters |
spellingShingle |
Improving virtual machine consolidation for heterogeneous cloud computing datacenters Rodrigues, Joao Antonio Magri [UNESP] Cloud computing Heterogeneous systems Virtual machine placement |
title_short |
Improving virtual machine consolidation for heterogeneous cloud computing datacenters |
title_full |
Improving virtual machine consolidation for heterogeneous cloud computing datacenters |
title_fullStr |
Improving virtual machine consolidation for heterogeneous cloud computing datacenters |
title_full_unstemmed |
Improving virtual machine consolidation for heterogeneous cloud computing datacenters |
title_sort |
Improving virtual machine consolidation for heterogeneous cloud computing datacenters |
author |
Rodrigues, Joao Antonio Magri [UNESP] |
author_facet |
Rodrigues, Joao Antonio Magri [UNESP] De Oliveira, Fabiola Martins C. Lobato, Renata Spolon [UNESP] Spolon, Roberta [UNESP] Manacero, Aleardo [UNESP] Borin, Edson |
author_role |
author |
author2 |
De Oliveira, Fabiola Martins C. Lobato, Renata Spolon [UNESP] Spolon, Roberta [UNESP] Manacero, Aleardo [UNESP] Borin, Edson |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Universidade Estadual de Campinas (UNICAMP) |
dc.contributor.author.fl_str_mv |
Rodrigues, Joao Antonio Magri [UNESP] De Oliveira, Fabiola Martins C. Lobato, Renata Spolon [UNESP] Spolon, Roberta [UNESP] Manacero, Aleardo [UNESP] Borin, Edson |
dc.subject.por.fl_str_mv |
Cloud computing Heterogeneous systems Virtual machine placement |
topic |
Cloud computing Heterogeneous systems Virtual machine placement |
description |
Datacenters in cloud computing systems may consist of thousands of computing nodes and communication devices, requiring virtual machine placement to optimize resources utilization. Heterogeneous environments of current datacenters have not been properly evaluated yet when the number of processing nodes and network devices is considered. This paper presents an approach to place virtual machines to minimize both the number of employed computing nodes and communication costs in heterogeneous environments. We evaluate our results against other known algorithms to show the efficiency of the proposed approach, which outperforms a state-of-the-art algorithm with a result of up to 13% better for network improvement while achieves the same number of computing nodes. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10-01 2020-12-12T01:50:56Z 2020-12-12T01:50:56Z |
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 |
http://dx.doi.org/10.1109/SBAC-PAD.2019.00037 Proceedings - Symposium on Computer Architecture and High Performance Computing, v. 2019-October, p. 176-179. 1550-6533 http://hdl.handle.net/11449/199848 10.1109/SBAC-PAD.2019.00037 2-s2.0-85076883130 |
url |
http://dx.doi.org/10.1109/SBAC-PAD.2019.00037 http://hdl.handle.net/11449/199848 |
identifier_str_mv |
Proceedings - Symposium on Computer Architecture and High Performance Computing, v. 2019-October, p. 176-179. 1550-6533 10.1109/SBAC-PAD.2019.00037 2-s2.0-85076883130 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings - Symposium on Computer Architecture and High Performance Computing |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
176-179 |
dc.source.none.fl_str_mv |
Scopus 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 |
|
_version_ |
1808128672042844160 |