Multicast with cache (Mcache): an adaptive zero-delay video-on-demand service

A closed-loop (demand-driven) approach toward video-on-demand services, called multicast cache (Mcache), is discussed. Servers use multicast to reduce their bandwidth usage by allowing multiple requests to be served with a single data stream. However, this requires clients to delay receiving the movie until the multicast starts. Using regional cache servers deployed over many strategic locations, Mcache can remove the initial playout delays of clients in multicast-based video streaming. While requests are batched together for a multicast, clients can receive the prefix of a requested movie clip from caches located in their own regions. The multicast containing the later portion of the movie can wait until the prefix is played out. While this use of regional caches has been proposed previously, the novelty of our scheme lies in that the requests coming after the multicast starts can still be batched together to be served by multicast patches without any playout delays. The use of patches was proposed before, but they are used either with unicast or with playout delays. Mcache effectively hires the idea of a multicast patch with caches to provide a truly adaptive video-on demand service whose bandwidth usage is up to par with the best known open-loop schemes under high request rates while using only minimal bandwidth under low request rates. In addition, efficient use of multicast and caches removes the need for a priori knowledge of client disk storage requirements which some of the existing schemes assume. This makes Mcache ideal for the current heterogeneous Internet environments where those parameters are hard to predict. We further propose the Segmented Mcache (SMcache) scheme which is a generalized and improved version of Mcache where the clip is partitioned into several segments in order to preserve the advantages of the original Mcache scheme with nearly the same server bandwidth requirement as the open loop schemes under high request rates.

[1]  Mary K. Vernon,et al.  Dynamic Skyscraper Broadcasts for Video-on-Demand , 1998, Multimedia Information Systems.

[2]  Philip S. Yu,et al.  On optimal batching policies for video-on-demand storage servers , 1996, Proceedings of the Third IEEE International Conference on Multimedia Computing and Systems.

[3]  Donald F. Towsley,et al.  Efficient schemes for broadcasting popular videos , 2002, Multimedia Systems.

[4]  Mary K. Vernon,et al.  Optimal and efficient merging schedules for video-on-demand servers , 1999, MULTIMEDIA '99.

[5]  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.

[6]  Yitzhak Birk,et al.  Tailored transmissions for efficient near-video-on-demand service , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[7]  Mary K. Vernon,et al.  Minimizing Bandwidth Requirements for On-Demand Data Delivery , 2001, IEEE Trans. Knowl. Data Eng..

[8]  Li-Ming Tseng,et al.  Harmonic broadcasting for video-on-demand service , 1997, IEEE Trans. Broadcast..

[9]  Kien A. Hua,et al.  Virtual Batching: A New Scheduling Technique for Video-on-Demand Servers , 1997, DASFAA.

[10]  Darrell D. E. Long,et al.  A low bandwidth broadcasting protocol for video on demand , 1998, Proceedings 7th International Conference on Computer Communications and Networks (Cat. No.98EX226).

[11]  Donald F. Towsley,et al.  Supplying instantaneous video-on-demand services using controlled multicast , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

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

[13]  Mary K. Vernon,et al.  Bandwidth skimming: a technique for cost-effective video on demand , 1999, Electronic Imaging.

[14]  Donald F. Towsley,et al.  Catching and selective catching: efficient latency reduction techniques for delivering continuous multimedia streams , 1999, MULTIMEDIA '99.

[15]  Shuang Deng,et al.  Empirical model of WWW document arrivals at access link , 1996, Proceedings of ICC/SUPERCOMM '96 - International Conference on Communications.

[16]  Asit Dan,et al.  Generalized interval caching policy for mixed interactive and long video workloads , 1996, Electronic Imaging.

[17]  Darrell D. E. Long,et al.  Zero-delay broadcasting protocols for video-on-demand , 1999, MULTIMEDIA '99.

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

[19]  Donald F. Towsley,et al.  Proxy prefix caching for multimedia streams , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[20]  John C. S. Lui,et al.  Reducing I/O demand in video-on-demand storage servers , 1995, SIGMETRICS '95/PERFORMANCE '95.

[21]  Ki-Dong Chung,et al.  A prefetching scheme based on the analysis of user access patterns in news-on-demand system , 1999, MULTIMEDIA '99.

[22]  Lixin Gao,et al.  Optimal Patching Schemes for Efficient Multimedia Streaming , 1999 .

[23]  Ying Cai,et al.  Optimizing patching performance , 1998, Electronic Imaging.

[24]  Mary K. Vernon,et al.  Optimized regional caching for on-demand data delivery , 1998, Electronic Imaging.

[25]  Kien A. Hua,et al.  Skyscraper broadcasting: a new broadcasting scheme for metropolitan video-on-demand systems , 1997, SIGCOMM '97.