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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Main Authors: Guangjie Han, Wenhui Que, Gangyong Jia, Lei Shu
Format: Article
Language:English
Published: MDPI AG 2016-02-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/16/2/246
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author Guangjie Han
Wenhui Que
Gangyong Jia
Lei Shu
author_facet Guangjie Han
Wenhui Que
Gangyong Jia
Lei Shu
author_sort Guangjie Han
collection DOAJ
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 doaj.art-cdd2a006a15e476db37f5d0e1f858be12022-12-22T04:04:00ZengMDPI AGSensors1424-82202016-02-0116224610.3390/s16020246s16020246An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud ComputingGuangjie Han0Wenhui Que1Gangyong Jia2Lei Shu3Department of Information and Communication Systems, Hohai University, 200 North Jinling Road, Changzhou 213022, ChinaDepartment of Information and Communication Systems, Hohai University, 200 North Jinling Road, Changzhou 213022, ChinaDepartment of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, ChinaGuangdong Petrochemical Equipment Fault Diagnosis Key Laboratory, Guangdong University of Petrochemical Technology, Guangdong 525000, ChinaCloud 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.http://www.mdpi.com/1424-8220/16/2/246multimedia cloud computingvirtual machine (VM) migrationenergy consumptionQoS
spellingShingle Guangjie Han
Wenhui Que
Gangyong Jia
Lei Shu
An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing
Sensors
multimedia cloud computing
virtual machine (VM) migration
energy consumption
QoS
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 multimedia cloud computing
virtual machine (VM) migration
energy consumption
QoS
url http://www.mdpi.com/1424-8220/16/2/246
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