On a unified architecture for video-on-demand services

Current video-on-demand (VoD)) systems can be classified into two categories: 1) true-Voll) (TVoD) and 2) near-VoD (NVod)). TVoD systems allocate a dedicated channel for every user to achieve short response times so that the user can select what video to play, when to play it, and perform interactive VCR-like controls at will. By contrast, NVoD systems transmit videos repeatedly over multiple broadcast or multicast channels to enable multiple users to share a single video channel so that system cost can be substantially reduced. The tradeoffs are limited video selections, fixed playback schedule, and limited or no interactive control. TVoD systems can be considered as one extreme where service quality is maximized, while NVoD systems can be considered as the other extreme where system cost is minimized. This paper proposes a novel architecture called Unified VoD) (UVoD) that can be configured to achieve cost-performance tradeoff anywhere between the two extremes (i.e., TVoD and NVoD). Assuming that a video client can concurrently receive two video channels and has local buffers for caching a portion of the video data, the proposed UVoD architecture can achieve significant performance gains (e.g., 400% more capacity for a 500-channel system) over TVoD under the same latency constraint. This paper presents the UVoD architecture, establishes a performance model, and analyzes UVoD's performance via numerical and simulation results.

[1]  Tomasz Imielinski,et al.  Metropolitan area video-on-demand service using pyramid broadcasting , 1996, Multimedia Systems.

[2]  Ho Kyun Park,et al.  Multicast delivery for interactive video-on-demand service , 1998, Proceedings Twelfth International Conference on Information Networking (ICOIN-12).

[3]  Kevin C. Almeroth,et al.  The Use of Multicast Delivery to Provide a Scalable and Interactive Video-on-Demand Service , 1996, IEEE J. Sel. Areas Commun..

[4]  Darrell D. E. Long,et al.  Improving video-on-demand server efficiency through stream tapping , 1997, Proceedings of Sixth International Conference on Computer Communications and Networks.

[5]  Borko Furht,et al.  Techniques for improving the capacity of video-on-demand systems , 1996, Proceedings of HICSS-29: 29th Hawaii International Conference on System Sciences.

[6]  Tzi-cker Chiueh,et al.  Periodic broadcasting approach to video-on-demand service , 1996, Other Conferences.

[7]  Asit Dan,et al.  Scheduling policies for an on-demand video server with batching , 1994, MULTIMEDIA '94.

[8]  Kang G. Shin,et al.  Providing unrestricted VCR functions in multicast video-on-demand servers , 1998, Proceedings. IEEE International Conference on Multimedia Computing and Systems (Cat. No.98TB100241).

[9]  Philip S. Yu,et al.  On optimal piggyback merging policies for video-on-demand systems , 1996, SIGMETRICS '96.

[10]  Wanjiun Liao,et al.  The Split and Merge Protocol for Interactive Video-on-Demand , 1997, IEEE Multim..

[11]  Arnold O. Allen,et al.  Probability, statistics and queueing theory - with computer science applications (2. ed.) , 1981, Int. CMG Conference.

[12]  Philip S. Yu,et al.  Exploring wait tolerance in effective batching for video-on-demand scheduling , 1998, Multimedia Systems.

[13]  Chong-kwon Kim,et al.  Multicast scheduling for VOD services , 2004, Multimedia Tools and Applications.

[14]  Shiao-Li Tsao,et al.  An Efficient Storage Server For Near Video-on-demand Systems , 1997, 1997 International Conference on Consumer Electronics.

[15]  Eric Wing Ming Wong,et al.  Performance Model of Interactive Video-on-Demand Systems , 1996, IEEE J. Sel. Areas Commun..

[16]  Philip S. Yu,et al.  A permutation-based pyramid broadcasting scheme for video-on-demand systems , 1996, Proceedings of the Third IEEE International Conference on Multimedia Computing and Systems.