Title :
CloudStreamMedia: A Cloud Assistant Global Video on Demand Leasing Scheme
Author :
Da Deng ; Zhihui Lu ; Wei Fang ; Jie Wu
Author_Institution :
Sch. of Comput. Sci., Fudan Univ., Shanghai, China
fDate :
June 28 2013-July 3 2013
Abstract :
Cloud computing is a new computing paradigm that takes all resources as services, and it is not only agile, but also scalable. With the development of cloud computing, video on demand has become one of the most popular applications over the Internet. Currently, there is a trend of using cloud data centers and virtualization technologies to expand large-scale video streaming services with higher quality and lower expense. In this paper, we present CSM (Cloud Stream Media), a scheme that books the minimum resources from global data centers to match its demand and dynamically adjusts all resources to effectively meet the users´ requests and guarantee a certain kind of quality of service, thus enhances the utilization and decreases the cost. CSM first predicts the stream media´s future demand and data center´s workload by using ARIMA model, and then performs a locality-aware resource booking (LARB) algorithm to lease the necessary resource from globalized cloud service providers in a long time. In order to handle prediction inaccuracy and the short-term demand peeks, CMS also introduces an inaccurate prediction handle strategy and performs auto scaling. We evaluate our scheme by combining both real world data and simulation. The results show good accuracy of our prediction and about 20% cut of total cost.
Keywords :
autoregressive moving average processes; cloud computing; computer centres; multimedia computing; quality of service; video on demand; video streaming; virtualisation; ARIMA model; CSM; Internet; LARB algorithm; auto scaling; cloud assistant global video on demand leasing scheme; cloud computing; cloud data center; cloud resource prediction; cloud stream media; global cloud service provider; global data center; locality aware resource booking; media streaming; quality of service; video streaming service; virtualization technology; Cloud computing; Computational modeling; Data models; Prediction algorithms; Predictive models; Quality of service; Streaming media; cloud computing; cloud resource prediction; resource leasing; streaming media; video on demand;
Conference_Titel :
Services Computing (SCC), 2013 IEEE International Conference on
Conference_Location :
Santa Clara, CA
Print_ISBN :
978-0-7695-5026-8
DOI :
10.1109/SCC.2013.91