Title of article :
QoS-Aware Virtual Machine Scheduling for Video Streaming Services in Multi-Cloud
Author/Authors :
Chen, Wei Tsinghua University - Research Institute of Information Technology - Tsinghua National Laboratory for Information Science and Technology, China , Cao, Junwei Tsinghua University - Research Institute of Information Technology - Tsinghua National Laboratory for Information Science and Technology, China , Wan, Yuxin Tsinghua University - Research Institute of Information Technology - Tsinghua National Laboratory for Information Science and Technology, China
Abstract :
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 multicloud 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.
Keywords :
cloud computing , dynamic scheduling , data centers , video streaming , service computing , performanceevaluation , Quality of Service (QoS)
Journal title :
Tsinghua Science and Technology
Journal title :
Tsinghua Science and Technology