Title :
Data Partitioning for Video-on-Demand Services
Author :
Bairong Lei ; Surya, Ivan ; Kamali, Saman ; Daudjee, Khuzaima
Author_Institution :
David R. Cheriton Sch. of Comput. Sci., Univ. of Waterloo, Waterloo, ON, Canada
Abstract :
Streaming video over the Internet has become a popular service that is projected to outstrip demand over most other real-time streaming services. Thus, it is essential to provide scalable server storage and services without which video-on-demand services will not be able to provide good performance in the face of increasing demand. In this paper, we study algorithms, and propose one, for simple partitioning video-on-demand storage to distribute content and workload among servers within a master-slave architecture. We show the effectiveness of the partitioning strategies by conducting experiments on an actual system to quantify trade-offs between the algorithms.
Keywords :
Internet; Web services; client-server systems; computer network performance evaluation; storage management; video on demand; video servers; video streaming; Internet; content distribution; data partitioning strategy; master-slave architecture; real-time streaming services; scalable server services; scalable server storage; video streaming; video-on-demand services; video-on-demand storage partitioning; workload distribution; Algorithm design and analysis; Approximation algorithms; Greedy algorithms; Load management; Partitioning algorithms; Servers; Streaming media; Data Partitioning; Load Balancing; Video files; Video-on-Demand Services;
Conference_Titel :
Network Computing and Applications (NCA), 2013 12th IEEE International Symposium on
Conference_Location :
Cambridge, MA
Print_ISBN :
978-0-7695-5043-5
DOI :
10.1109/NCA.2013.41
