QoS-Aware Virtual Machine Scheduling for Video Streaming Services in Multi-Cloud

来源 :Tsinghua Science and Technology | 被引量 : 0次 | 上传用户:li1xiang125
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Video streaming services are trending to be deployed on cloud. Cloud computing offers better stability and lower price than traditional IT facilities. Huge storage capacity is essential for video streaming service. More and more cloud providers appear so there are increasing cloud platforms to choose. A better choice is to use more than one data center, which is called multi-cloud. In this paper a closed-loop approach is proposed for optimizing Quality of Service (QoS) and cost. Modules of monitoring and controlling data centers are required as well as the application feedback such as video streaming services. An algorithm is proposed to help choose cloud providers and data centers in a multi-cloud environment as a video service manager. Performance with different video service workloads are evaluated. Compared with using only one cloud provider, dynamically deploying services in multi-cloud is better in aspects of both cost and QoS. If cloud service costs are different among data centers, the algorithm will help make choices to lower the cost and keep a high QoS. Video streaming services are trending to be deployed on cloud. Cloud computing offers better stability and lower price than traditional IT facilities. Huge storage capacity is essential for video streaming service. More and more cloud providers appear so there are increasing cloud platforms to choose. A better this is better than one data center, which is called multi-cloud. In this paper a closed-loop approach is proposed for optimizing Quality of Service (QoS) and cost. Modules of monitoring and controlling data centers are required as well as the application feedback such as video streaming services. An algorithm is proposed to help choose cloud providers and data centers in a multi-cloud environment as a video service manager. Performance with different video service workloads are. , dynamically deploying services in multi-cloud is better in aspects of both cost and QoS. If cloud service costs are different among data cent ers, the algorithm will help make choices to lower the cost and keep a high QoS.
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