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 accu...

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Bibliographic Details
Published in:IEEE transactions on multimedia 2008-01, Vol.10 (1), p.153-159
Main Authors: Jun Guo, Wong, E.W.M., Chan, S., Taylor, P., Zukerman, M., Kit-Sang Tang
Format: Article
Language:English
Subjects:
Applied sciences
Blocking probability
Capacity planning
Computer science
control theory
systems
Computer systems and distributed systems. User interface
Constraint optimization
Design optimization
Disks
Exact sciences and technology
fixed-point approximation
Large-scale systems
Mathematical analysis
Mathematics
Motion pictures
Multimedia
Optimization
Performance analysis
Performance evaluation
resource selection
Servers
Software
Statistics
Tasks
Testing
Video on demand
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Description
Summary: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.
ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2007.911281