期刊
SENSORS
卷 16, 期 2, 页码 -出版社
MDPI
DOI: 10.3390/s16020246
关键词
multimedia cloud computing; virtual machine (VM) migration; energy consumption; QoS
资金
- Qing Lan Project
- National Natural Science Foundation of China [61572172, 61401107]
- Open Fund through the Guangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis [PEFD2015-06]
- Special Fund of Guangdong Higher School Talent Recruitment
- top Level Talents Project in Sailing Plan of Guangdong Province
- Guangdong Province Outstanding Young Professor Project
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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