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Sensors 2016, 16(2), 246; doi:10.3390/s16020246

An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing

1
Department of Information and Communication Systems, Hohai University, 200 North Jinling Road, Changzhou 213022, China
2
Department of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China
3
Guangdong Petrochemical Equipment Fault Diagnosis Key Laboratory, Guangdong University of Petrochemical Technology, Guangdong 525000, China
*
Author to whom correspondence should be addressed.
Academic Editor: Antonio Jara
Received: 7 January 2016 / Revised: 2 February 2016 / Accepted: 14 February 2016 / Published: 18 February 2016
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
View Full-Text   |   Download PDF [3147 KB, uploaded 18 February 2016]   |  

Abstract

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. View Full-Text
Keywords: multimedia cloud computing; virtual machine (VM) migration; energy consumption; QoS multimedia cloud computing; virtual machine (VM) migration; energy consumption; QoS
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MDPI and ACS Style

Han, G.; Que, W.; Jia, G.; Shu, L. An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing. Sensors 2016, 16, 246.

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