Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Video Database Techniques and Video-on-Demand

Video Database Techniques and Video-on-Demand
View Sample PDF
Author(s): Jen-Wen Ding (Kun Shan University of Technology, Taiwan), Yueh-Min Huang (National Cheng Kung University, Taiwan), Sheng-Yuan Zeng (National Cheng Kung University, Taiwan) and Chang-Chung Chu (Tunghai University, Taiwan)
Copyright: 2002
Pages: 14
Source title: Distributed Multimedia Databases: Techniques and Applications
Source Author(s)/Editor(s): Timothy K. Shih (Tamkang University, Taiwan)
DOI: 10.4018/978-1-930708-29-7.ch009


View Video Database Techniques and Video-on-Demand on the publisher's website for pricing and purchasing information.


Generally, a large-scale video server is composed of numerous disk striping groups. The striping policies employed by each disk striping group largely determine the performance of a video server. For storage and transmission efficiency, video data are usually compressed using variable-bit-rate (VBR) encoding algorithms, such as JPEG and MPEG. The amount of data consumed by a VBR video stream varies with time. This property, when coupled with striping, unfortunately, results in load imbalance across disks, degrading the overall server performance significantly. This chapter focuses on VBR video striping. It presents two state-of-the-art VBR striping schemes proposed in the literature: one is designed for homogeneous disks and the other is designed for heterogeneous disks. To gain insights into VBR striping, this chapter also develops performance models for the two striping policies. With these performance models, system designers can predict the maximum service capacity of a server, perform online admission control for clients, and optimize the performance of a server, without performing exhaustive tests on a real-system.

Related Content

K. Jairam Naik, Annukriti Soni. © 2021. 18 pages.
Randhir Kumar, Rakesh Tripathi. © 2021. 22 pages.
Yogesh Kumar Gupta. © 2021. 38 pages.
Kamel H. Rahouma, Ayman A. Ali. © 2021. 34 pages.
Muni Sekhar Velpuru. © 2021. 19 pages.
Vijayakumari B.. © 2021. 24 pages.
Neetu Faujdar, Anant Joshi. © 2021. 41 pages.
Body Bottom