Scalable media streaming to interactive users

Recently, a number of scalable stream sharing protocols have been proposed with the promise of great reductions in the server and network bandwidth required for delivering popular media content. Although the scalability of these protocols has been evaluated mostly for sequential user accesses, a high degree of interactivity has been observed in the accesses to several real media servers. Moreover, some studies have indicated that user interactivity can severely penalize the scalability of stream sharing protocols.This paper investigates alternative mechanisms for scalable streaming to interactive users. We first identify a set of workload aspects that are determinant to the scalability of classes of streaming protocols. Using real workloads and a new interactive media workload generator, we build a rich set of realistic synthetic workloads. We evaluate Bandwidth Skimming and Patching, two state-of-the-art streaming protocols, covering, with our workloads, a larger region of the design space than previous work. Finally, we propose and evaluate five optimizations to Bandwidth Skimming, the most scalable of the two protocols. Our best optimization reduces the average server bandwidth required for interactive workloads in up to 54%, for unlimited client buffers, and 29%, if buffers are constrained to 25% of media size.

[1]  Alec Wolman,et al.  Measurement and Analysis of a Streaming Media Workload , 2001, USITS.

[2]  Jitendra Padhye,et al.  Continuous-Media Courseware Server: A Study of Client Interactions , 1999, IEEE Internet Comput..

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

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

[5]  Predrag R. Jelenkovic,et al.  The Dyadic Stream Merging Algorithm , 2002, J. Algorithms.

[6]  Kang G. Shin,et al.  Best-Effort Patching for Multicast True VoD Service , 2005, Multimedia Tools and Applications.

[7]  Azer Bestavros,et al.  Scalability of multicast delivery for non-sequential streaming access , 2002, SIGMETRICS '02.

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

[9]  Prashant J. Shenoy,et al.  Periodic broadcast and patching services: implementation, measurement, and analysis in an Internet streaming video testbed , 2001, SIGMETRICS '01.

[10]  Mary K. Vernon,et al.  Network bandwidth requirements for scalable on-demand streaming , 2007, TNET.

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

[12]  Ítalo S. Cunha,et al.  Analyzing client interactivity in streaming media , 2004, WWW '04.

[13]  Tatsuya Suda,et al.  Source-adaptive multilayered multicast algorithms for real-time video distribution , 2000, TNET.

[14]  Mary K. Vernon,et al.  Analysis of educational media server workloads , 2001, NOSSDAV '01.

[15]  Jiangchuan Liu,et al.  Proxy caching for media streaming over the Internet , 2004, IEEE Communications Magazine.

[16]  Richard E. Ladner,et al.  Competitive on-line stream merging algorithms for media-on-demand , 2001, SODA '01.

[17]  Mary K. Vernon,et al.  Quality of service evaluations of multicast streaming protocols , 2002, SIGMETRICS '02.

[18]  Mary K. Vernon,et al.  Delimiting the range of effectiveness of scalable on-demand streaming , 2002, Perform. Evaluation.