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An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing

Cloud computing has innovated the IT industry in recent years, as it can delivery subscription-based services to users in the pay-as-you-go model. Meanwhile, multimedia cloud computing is emerging based on cloud computing to provide a variety of media services on the Internet. However, with the grow...

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Autores principales: Han, Guangjie, Que, Wenhui, Jia, Gangyong, Shu, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801622/
https://www.ncbi.nlm.nih.gov/pubmed/26901201
http://dx.doi.org/10.3390/s16020246
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author Han, Guangjie
Que, Wenhui
Jia, Gangyong
Shu, Lei
author_facet Han, Guangjie
Que, Wenhui
Jia, Gangyong
Shu, Lei
author_sort Han, Guangjie
collection PubMed
description Cloud computing has innovated the IT industry in recent years, as it can delivery subscription-based services to users in the pay-as-you-go model. Meanwhile, multimedia cloud computing is emerging based on cloud computing to provide a variety of media services on the Internet. However, with the growing popularity of multimedia cloud computing, its large energy consumption cannot only contribute to greenhouse gas emissions, but also result in the rising of cloud users’ costs. Therefore, the multimedia cloud providers should try to minimize its energy consumption as much as possible while satisfying the consumers’ resource requirements and guaranteeing quality of service (QoS). In this paper, we have proposed a remaining utilization-aware (RUA) algorithm for virtual machine (VM) placement, and a power-aware algorithm (PA) is proposed to find proper hosts to shut down for energy saving. These two algorithms have been combined and applied to cloud data centers for completing the process of VM consolidation. Simulation results have shown that there exists a trade-off between the cloud data center’s energy consumption and service-level agreement (SLA) violations. Besides, the RUA algorithm is able to deal with variable workload to prevent hosts from overloading after VM placement and to reduce the SLA violations dramatically.
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spelling pubmed-48016222016-03-25 An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing Han, Guangjie Que, Wenhui Jia, Gangyong Shu, Lei Sensors (Basel) Article Cloud computing has innovated the IT industry in recent years, as it can delivery subscription-based services to users in the pay-as-you-go model. Meanwhile, multimedia cloud computing is emerging based on cloud computing to provide a variety of media services on the Internet. However, with the growing popularity of multimedia cloud computing, its large energy consumption cannot only contribute to greenhouse gas emissions, but also result in the rising of cloud users’ costs. Therefore, the multimedia cloud providers should try to minimize its energy consumption as much as possible while satisfying the consumers’ resource requirements and guaranteeing quality of service (QoS). In this paper, we have proposed a remaining utilization-aware (RUA) algorithm for virtual machine (VM) placement, and a power-aware algorithm (PA) is proposed to find proper hosts to shut down for energy saving. These two algorithms have been combined and applied to cloud data centers for completing the process of VM consolidation. Simulation results have shown that there exists a trade-off between the cloud data center’s energy consumption and service-level agreement (SLA) violations. Besides, the RUA algorithm is able to deal with variable workload to prevent hosts from overloading after VM placement and to reduce the SLA violations dramatically. MDPI 2016-02-18 /pmc/articles/PMC4801622/ /pubmed/26901201 http://dx.doi.org/10.3390/s16020246 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Han, Guangjie
Que, Wenhui
Jia, Gangyong
Shu, Lei
An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing
title An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing
title_full An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing
title_fullStr An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing
title_full_unstemmed An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing
title_short An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing
title_sort efficient virtual machine consolidation scheme for multimedia cloud computing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801622/
https://www.ncbi.nlm.nih.gov/pubmed/26901201
http://dx.doi.org/10.3390/s16020246
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