Receiver-driven layered multicast
Conference proceedings on Applications, technologies, architectures, and protocols for computer communications
An adaptive protocol for synchronizing media streams
Multimedia Systems
CHIME: a metadata-based distributed software development environment
ESEC/FSE-7 Proceedings of the 7th European software engineering conference held jointly with the 7th ACM SIGSOFT international symposium on Foundations of software engineering
Video Processing and Communications
Video Processing and Communications
Adaptive Video Multicast over the Internet
IEEE MultiMedia
Using process technology to control and coordinate software adaptation
Proceedings of the 25th International Conference on Software Engineering
Using Little-JIL to Coordinate Agents in Software Engineering
ASE '00 Proceedings of the 15th IEEE international conference on Automated software engineering
Lightweight Stream Synchronization Framework for Multimedia Collaborative Applications
ISCC '00 Proceedings of the Fifth IEEE Symposium on Computers and Communications (ISCC 2000)
Design and Evaluation of MiMaze, a Multi-Player Game on the Internet
ICMCS '98 Proceedings of the IEEE International Conference on Multimedia Computing and Systems
Orchestrating the dynamic adaptation of distributed software with process technology
Orchestrating the dynamic adaptation of distributed software with process technology
Retrofitting Autonomic Capabilities onto Legacy Systems
Cluster Computing
IEEE Journal on Selected Areas in Communications
Overview of fine granularity scalability in MPEG-4 video standard
IEEE Transactions on Circuits and Systems for Video Technology
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The increasing popularity of online courses has highlighted the lack of collaborative tools for student groups. In addition, the introduction of lecture videos into the online curriculum has drawn attention to the disparity in the network resources used by students. We present an e-Learning architecture and adaptation model called AI2TV (Adaptive Internet Interactive Team Video), which allows virtual students, possibly some or all disadvantaged in network resources, to collaboratively view a video in synchrony. AI2TV upholds the invariant that each student will view semantically equivalent content at all times. Video player actions, like play, pause and stop, can be initiated by any student and their results are seen by all the other students. These features allow group members to review a lecture video in tandem, facilitating the learning process. Experimental trials show that AI2TV can successfully synchronize video for distributed students while, at the same time, optimizing the video quality, given fluctuating bandwidth, by adaptively adjusting the quality level for each student.