Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM

Detalhes bibliográficos
Autor(a) principal: Castro, Pedro Henrique Pires de
Data de Publicação: 2014
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional da UFG
dARK ID: ark:/38995/00130000017tk
Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/4124
Resumo: Cloud computing is being consolidated as a new distributed systems paradigm, offering computing resources in a virtualized way and with unprecedented levels of flexibility, reliability, and scalability. Unfortunately, the benefits of cloud computing come at a high cost with regard to energy, mainly because of one of its core enablers, the data center. There are a number of proposals that seek to enhance energy efficiency in data centers. However, most of them focus only on the energy consumed by CPU and ignore the remaining hardware, e.g., RAM. In this work, we show the considerable impact that RAM can have on total energy consumption, particularly in servers with large amounts of this memory. We also propose three new approaches for dynamic consolidation of virtual machines (VMs) that take into account both CPU and RAM usage. We have implemented and evaluated our proposals in the CloudSim simulator using real-world traces and compared the results with state-of-the-art solutions. By adopting a wider view of the system, our proposals are able to reduce not only energy consumption but also the number of SLA violations, i.e., they provide a better service at a lower cost.
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spelling Cardoso, Kleber Vieirahttp://lattes.cnpq.br/0268732896111424Corrêa, Sand LuzCardoso, Kleber VieiraCorrêa, Sand LuzCosta, Fábio MoreiraGranville, Lisandro Zambenedettihttp://lattes.cnpq.br/6103331429341084Castro, Pedro Henrique Pires de2015-02-05T20:00:48Z2014-08-04CASTRO, P. H. P. Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM. 2014. 86 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2014.http://repositorio.bc.ufg.br/tede/handle/tede/4124ark:/38995/00130000017tkCloud computing is being consolidated as a new distributed systems paradigm, offering computing resources in a virtualized way and with unprecedented levels of flexibility, reliability, and scalability. Unfortunately, the benefits of cloud computing come at a high cost with regard to energy, mainly because of one of its core enablers, the data center. There are a number of proposals that seek to enhance energy efficiency in data centers. However, most of them focus only on the energy consumed by CPU and ignore the remaining hardware, e.g., RAM. In this work, we show the considerable impact that RAM can have on total energy consumption, particularly in servers with large amounts of this memory. We also propose three new approaches for dynamic consolidation of virtual machines (VMs) that take into account both CPU and RAM usage. We have implemented and evaluated our proposals in the CloudSim simulator using real-world traces and compared the results with state-of-the-art solutions. By adopting a wider view of the system, our proposals are able to reduce not only energy consumption but also the number of SLA violations, i.e., they provide a better service at a lower cost.A computação em nuvem tem levado os sistemas distribuídos a um novo patamar, oferecendo recursos computacionais de forma virtualizada, flexível, robusta e escalar. Essas vantagens, no entanto, surgem juntamente com um alto consumo de energia nos centros de dados, ambientes que podem ter até centenas de milhares de servidores. Existem muitas propostas para alcançar eficiência energética em centros de dados para computação em nuvem. Entretanto, muitas propostas consideram apenas o consumo proveniente do uso de CPU e ignoram os demais componentes de hardware, e.g., RAM. Neste trabalho, mostramos o impacto considerável que RAM pode ter sobre o consumo total de energia, principalmente em servidores com grandes quantidades dessa memória. Também propomos três novas abordagens para consolidação dinâmica de máquinas virtuais, levando em conta tanto o consumo de CPU quanto de RAM. Nossas propostas foram implementadas e avaliadas no simulador CloudSim utilizando cargas de trabalho do mundo real. Os resultados foram comparados com soluções do estado-da-arte. Pela adoção de uma visão mais ampla do sistema, nossas propostas não apenas são capazes de reduzir o consumo de energia como também reduzem violações de SLA, i.e., proveem um serviço melhor a um custo mais baixo.Submitted by Erika Demachki (erikademachki@gmail.com) on 2015-02-05T19:59:39Z No. of bitstreams: 2 Dissertação - Pedro Henrique Pires de Castro - 2014.pdf: 1908182 bytes, checksum: edac87bddd8346a2bcce5d9b5f00301d (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)Approved for entry into archive by Erika Demachki (erikademachki@gmail.com) on 2015-02-05T20:00:48Z (GMT) No. of bitstreams: 2 Dissertação - Pedro Henrique Pires de Castro - 2014.pdf: 1908182 bytes, checksum: edac87bddd8346a2bcce5d9b5f00301d (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)Made available in DSpace on 2015-02-05T20:00:48Z (GMT). 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dc.title.eng.fl_str_mv Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM
dc.title.alternative.eng.fl_str_mv Strategies for efficient usage of resources in data centers considering the consumption of CPU and RAM
title Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM
spellingShingle Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM
Castro, Pedro Henrique Pires de
Computação em nuvem
Centro de dados
Eficiência energética
Cumprimento de SLA
Consolidação de máquinas virtuais
Cloud computing
Data center
Energy efficiency
SLA compliance
Virtual machine consolidation
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
title_short Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM
title_full Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM
title_fullStr Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM
title_full_unstemmed Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM
title_sort Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM
author Castro, Pedro Henrique Pires de
author_facet Castro, Pedro Henrique Pires de
author_role author
dc.contributor.advisor1.fl_str_mv Cardoso, Kleber Vieira
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/0268732896111424
dc.contributor.advisor-co1.fl_str_mv Corrêa, Sand Luz
dc.contributor.referee1.fl_str_mv Cardoso, Kleber Vieira
dc.contributor.referee2.fl_str_mv Corrêa, Sand Luz
dc.contributor.referee3.fl_str_mv Costa, Fábio Moreira
dc.contributor.referee4.fl_str_mv Granville, Lisandro Zambenedetti
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/6103331429341084
dc.contributor.author.fl_str_mv Castro, Pedro Henrique Pires de
contributor_str_mv Cardoso, Kleber Vieira
Corrêa, Sand Luz
Cardoso, Kleber Vieira
Corrêa, Sand Luz
Costa, Fábio Moreira
Granville, Lisandro Zambenedetti
dc.subject.por.fl_str_mv Computação em nuvem
Centro de dados
Eficiência energética
Cumprimento de SLA
Consolidação de máquinas virtuais
topic Computação em nuvem
Centro de dados
Eficiência energética
Cumprimento de SLA
Consolidação de máquinas virtuais
Cloud computing
Data center
Energy efficiency
SLA compliance
Virtual machine consolidation
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
dc.subject.eng.fl_str_mv Cloud computing
Data center
Energy efficiency
SLA compliance
Virtual machine consolidation
dc.subject.cnpq.fl_str_mv CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
description Cloud computing is being consolidated as a new distributed systems paradigm, offering computing resources in a virtualized way and with unprecedented levels of flexibility, reliability, and scalability. Unfortunately, the benefits of cloud computing come at a high cost with regard to energy, mainly because of one of its core enablers, the data center. There are a number of proposals that seek to enhance energy efficiency in data centers. However, most of them focus only on the energy consumed by CPU and ignore the remaining hardware, e.g., RAM. In this work, we show the considerable impact that RAM can have on total energy consumption, particularly in servers with large amounts of this memory. We also propose three new approaches for dynamic consolidation of virtual machines (VMs) that take into account both CPU and RAM usage. We have implemented and evaluated our proposals in the CloudSim simulator using real-world traces and compared the results with state-of-the-art solutions. By adopting a wider view of the system, our proposals are able to reduce not only energy consumption but also the number of SLA violations, i.e., they provide a better service at a lower cost.
publishDate 2014
dc.date.issued.fl_str_mv 2014-08-04
dc.date.accessioned.fl_str_mv 2015-02-05T20:00:48Z
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identifier_str_mv CASTRO, P. H. P. Estratégias para uso eficiente de recursos em centros de dados considerando consumo de CPU e RAM. 2014. 86 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2014.
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