Journal Home > Volume 18 , Issue 3
Tsinghua Science and Technology 2013, 18(3): 308-317 https://doi.org/10.1109/TST.2013.6522589
Open Access | Issue | Published: 03 June 2013

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

Show Author's Information Wei Chen,  Junwei Cao( ),  Yuxin Wan
Research Institute of Information Technology, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China
Keywords:
cloud computing, performance evaluation, data centers, service computing, dynamic scheduling, video streaming, Quality of Service (QoS)
Cite this article:
Chen W, Cao J, Wan Y. QoS-Aware Virtual Machine Scheduling for Video Streaming Services in Multi-Cloud. Tsinghua Science and Technology, 2013, 18(3): 308-317. https://doi.org/10.1109/TST.2013.6522589
Download citation
EndNote(RIS)
BibTeX

388

Views

44

Downloads

Citations

23

Crossref

N/A

WoS

26

Scopus

0

CSCD

Abstract Full text About this article

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.


menu
Abstract
Full text
Outline
About this article

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

Show Author's information Wei Chen, Junwei Cao( ), Yuxin Wan
Research Institute of Information Technology, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, 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 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.

Keywords: cloud computing, performance evaluation, data centers, service computing, dynamic scheduling, video streaming, Quality of Service (QoS)

References(15)

[1]
M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, and M. Zaharia, A view of cloud computing, Communications of the ACM, vol. 53, no. 4, pp. 50-58, 2010.
DOI Google Scholar
[2]
I. Foster, Y. Zhao, I. Raicu, and S. Lu, Cloud computing and grid computing 360-degree compared, presented at Grid Computing Environments Workshop, Austin, TX, USA, 2008.
DOI
[3]
M. A. AlZain, E. Pardede, B. Soh, and J. A. Thom, Cloud computing security: From single to multi-clouds, presented at System Science (HICSS), 2012 45th Hawaii International Conference on. IEEE, Maui, HI, USA, 2012.
DOI
[4]
Z. Chen, F. Han, J. Cao, and S. Chen, Cloud computing-based forensic analysis for collaborative network security management system, Tsinghua Science and Technology, vol. 18, no. 1, pp. 40-50, 2013.
DOI Google Scholar
[5]
R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility, Future Generation Computer Systems, vol. 25, no. 6, pp. 599-616, 2009.
DOI Google Scholar
[6]
D. Kondo, B. Javadi, P. Malecot, F. Cappello, and D. P. Anderson, Cost-benefit analysis of cloud computing versus desktop grids, presented at Parallel & Distributed Processing IPDPS 2009, Rome, Italy, 2009.
DOI
[7]
D. Yuan, Y. Yang, X. Liu, and J. Chen, A cost-effective strategy for intermediate data storage in scientific cloud workflow systems, presented at Parallel & Distributed Processing (IPDPS), 2010 IEEE International Symposium on, Atlanta, GA, USA, 2010.
DOI
[8]
J. Cao, K. Hwang, K. Li, and A. Y. Zomaya, Optimal multiserver configuration for profit maximization in cloud computing, IEEE Trans. Parallel and Distributed Systems, vol. 24, no. 6, pp. 1087-1096, 2013.
DOI Google Scholar
[9]
A. Sampaio and N. Mendonca, Uni4Cloud: An approach based on open standards for deployment and management of multi-cloud applications, in Processdings of the 2nd International Workshop on Software Engineering for Cloud Computing, New York, NY, USA, 2011.
DOI
[10]
J. L. L. Simarro, R. Moreno-Vozmediano, R. S. Montero, and I. M. Llorente, Dynamic placement of virtual machines for cost optimization in multi-cloud environments, in 2011 International Conference on High Performance Computing and Simulation (HPCS), Istanbul, Turkey, 2011.
DOI
[11]
J. Li, J. Chinneck, M. Woodside, M. Litoiu, G. Iszlai, Performance model driven QoS guarantees and optimization in clouds, presented at Software Engineering Challenges of Cloud Computing, ICSE Workshop on, Vancouver, BC, Canada, 2009.
DOI
[12]
D. Wu, Y. T. Hou, W. Zhu, Y. Q. Zhang, and J. M. Peha, Streaming video over the Internet: Approaches and directions, Circuits and Systems for Video Technology, IEEE Transactions on, vol. 11, no. 3, pp. 282-300, 2001.
DOI Google Scholar
[13]
S. Tao and R. Gurin, Application-specific path switching: A case study for streaming video, in Proceedings of the 12th Annual ACM International Conference on Multimedia, New York, NY, USA, 2004.
DOI
[14]
S. Tao, K. Xu, A. Estepa, T. F. L. Gao, R. O. C. H. Guerin, J. Kurose, and Z. L. Zhang, Improving VoIP quality through path switching, presented at 24th Annual Joint Conference of the IEEE Computer and Communications Societies, Philadelphia, PA, USA, 2005.
[15]
Y. Wu, C. Wu, B. Li, X. Qiu, and F. C. Lau, Cloudmedia: When cloud on demand meets video on demand, presented at Distributed Computing Systems (ICDCS), 2011 31st International Conference on, Minneapolis, MN, USA, 2011.
Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 16 May 2013
Accepted: 16 May 2013
Published: 03 June 2013
Issue date: June 2013

Copyright

© The author(s) 2013

Acknowledgements

This work was supported in part by National Key Basic Research and Development (973) Program of China (Nos. 2011CB302805 and 2013CB228206), the National High-Tech Research and Development (863) Program of China (No. 2013BAH19F01), and the National Natural Science Foundation of China (No. 61233016).

Rights and permissions

Return