DocumentCode :
585
Title :
Toward Optimal Deployment of Cloud-Assisted Video Distribution Services
Author :
Jian He ; Di Wu ; Yupeng Zeng ; Xiaojun Hei ; Yonggang Wen
Author_Institution :
Dept. of Comput. Sci., Sun Yat-Sen Univ., Guangzhou, China
Volume :
23
Issue :
10
fYear :
2013
fDate :
Oct. 2013
Firstpage :
1717
Lastpage :
1728
Abstract :
For Internet video services, the high fluctuation of user demands in geographically distributed regions results in low resource utilizations of traditional content distribution network systems. Due to the capability of rapid and elastic resource provisioning, cloud computing emerges as a new paradigm to reshape the model of video distribution over the Internet, in which resources (such as bandwidth, storage) can be rented on demand from cloud data centers to meet volatile user demands. However, it is challenging for a video service provider (VSP) to optimally deploy its distribution infrastructure over multiple geo-distributed cloud data centers. A VSP needs to minimize the operational cost induced by the rentals of cloud resources without sacrificing user experience in all regions. The geographical diversity of cloud resource prices further makes the problem complicated. In this paper, we investigate the optimal deployment problem of cloud-assisted video distribution services and explore the best tradeoff between the operational cost and the user experience. We aim to pave the way for building the next-generation video cloud. Toward this objective, we first formulate the deployment problem into a min-cost network flow problem, which takes both the operational cost and the user experience into account. Then, we apply the Nash bargaining solution to solve the joint optimization problem efficiently and derive the optimal bandwidth provisioning strategy and optimal video placement strategy. In addition, we extend the algorithms to the online case and consider the scenario when peers participate into video distribution. Finally, we conduct extensive simulations to evaluate our algorithms in the realistic settings. Our results show that our proposed algorithms can achieve a good balance among multiple objectives and effectively optimize both operational cost and user experience.
Keywords :
bandwidth allocation; cloud computing; game theory; multimedia systems; video streaming; Internet video services; Nash bargaining solution; VSP; cloud computing; cloud resource price; cloud-assisted video distribution services; content distribution network system; geo-distributed cloud data center; geographical diversity; min-cost network flow problem; next-generation video cloud; optimal bandwidth provisioning strategy; optimal deployment problem; optimal video placement strategy; video service provider; volatile user demand; Cloud deployment; Nash bargaining solution; video distribution;
fLanguage :
English
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1051-8215
Type :
jour
DOI :
10.1109/TCSVT.2013.2255423
Filename :
6490035
Link To Document :
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