Performance analysis of resource selection schemes for a large scale video-on-demand system

Download files
Access & Terms of Use
open access
Altmetric
Abstract
The designers of a large scale video-on-demand system face an optimization problem of deciding how to assign movies to multiple disks (servers) such that the request blocking probability is minimized subject to capacity constraints. To solve this problem, it is essential to develop scalable and accurate analytical means to evaluate the blocking performance of the system for a given file assignment. The performance analysis is made more complicated by the fact that the request blocking probability depends also on how disks are selected to serve user requests for multicopy movies. In this paper, we analyze several efficient resource selection schemes. Numerical results demonstrate that our analysis is scalable and sufficiently accurate to support the task of file assignment optimization in such a system. © 2008 IEEE.
Persistent link to this record
DOI
Link to Open Access Version
Additional Link
Author(s)
Guo, Jun
Wong, Eric
Chan, Sammy
Taylor, Peter
Zukerman, Moshe
Tang, Kit-Sang
Supervisor(s)
Creator(s)
Editor(s)
Translator(s)
Curator(s)
Designer(s)
Arranger(s)
Composer(s)
Recordist(s)
Conference Proceedings Editor(s)
Other Contributor(s)
Corporate/Industry Contributor(s)
Publication Year
2008
Resource Type
Journal Article
Degree Type
Files
download TMM08.pdf 318.67 KB Adobe Portable Document Format
Related dataset(s)