Scheduling policies for an on-demand video server with batching
MULTIMEDIA '94 Proceedings of the second ACM international conference on Multimedia
On optimal piggyback merging policies for video-on-demand systems
Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Metropolitan area video-on-demand service using pyramid broadcasting
Multimedia Systems
A digital fountain approach to reliable distribution of bulk data
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Optimal and efficient merging schedules for video-on-demand servers
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Efficient erasure correcting codes
IEEE Transactions on Information Theory
Optimized Distributed Delivery of Continuous-Media Documents over Unreliable Communication Links
IEEE Transactions on Parallel and Distributed Systems
Distributed middleware architectures for scalable media services
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
A bandwidth reduction method for selective contents broadcasting
International Journal of Advanced Media and Communication
Forward error correction for multipath media streaming
IEEE Transactions on Circuits and Systems for Video Technology
Connection mechanism using agent for streaming in multimedia messaging service environment
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
| Hi-index | 4.10 |
The challenges for streaming media today include the high data rates and significant bandwidth required for the uninterrupted delivery of high-quality music and video. Building a scalable and reliable system for on-demand and live streaming in this environment has proven difficult.By definition, a media-on-demand system lets clients freely access and play back media without interruption after a given start-up latency. The authors' system keeps the server's outgoing bandwidth independent of the number of clients, and each client behaves independently of other clients.Although most codecs tolerate a certain amount of data loss, a high loss rate can significantly affect playback quality. Even with router assistance to aggregate acknowledgments, for a sufficiently heterogeneous network and a large enough audience, at least one client will lose almost every packet. This requires retransmission, which causes delays and results in massive reception of duplicate packets.The authors' MoD system uses forward error correction codes to recover lost data. FEC uses the same redundant data to allow multiple clients to recover from different packet losses.