Performance Analysis of Resource Selection Schemes for a Large Scale Video-on-Demand System

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.

• Type: Journal
• Year: 2008
• Where: TMM
• Authors: Jun Guo, Eric Wing Ming Wong, Sammy Chan, Peter Taylor, Moshe Zukerman, Kit-Sang Tang
• Keywords: Accurate Analytical Means, File Assignment, Optimization Problem, TMM 2008