Performance study on media server scheduling in video-on-demand systems

Yinqing Zhao; C.-C. J. Jay Kuo

doi:10.1117/12.486820

8 August 2003 Performance study on media server scheduling in video-on-demand systems

Yinqing Zhao, C.-C. J. Jay Kuo

Proceedings Volume 5108, Visual Information Processing XII; (2003) https://doi.org/10.1117/12.486820
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Media server scheduling in video-on-demand systems includes video content allocation and request migration among servers. In this paper, we present a greedy algorithm to allocate video copies to media servers. It uses a graph model and minimizes the average shortest distance among media servers at each step. In order to study the request migration process, we introduce a state matrix representation that stores the service load information of each media server and plays an important role in the determination of migration paths. Based on this representation, we develop a state transition method to simulate the request migration process and calculate the performance metrics such as failure rates and service delay. The derived results match very well with numerical experiments. It is further demonstrated that the random early migration (REM) algorithm proposed in our previous work outperforms the normal migration scheme with lower failure rates and shorter service delay.

Citation Download Citation

Yinqing Zhao and C.-C. J. Jay Kuo "Performance study on media server scheduling in video-on-demand systems", Proc. SPIE 5108, Visual Information Processing XII, (8 August 2003); https://doi.org/10.1117/12.486820

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available