Response time and display rate in human performance with computers
ACM Computing Surveys (CSUR)
Groupware: some issues and experiences
Communications of the ACM
Log-based collaborative infrastructure
Log-based collaborative infrastructure
Using cursor prediction to smooth telepointer jitter
GROUP '03 Proceedings of the 2003 international ACM SIGGROUP conference on Supporting group work
Measurement based analysis, modeling, and synthesis of the internet delay space
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Improving network efficiency in real-time groupware with general message compression
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Modeling the effects of delayed haptic and visual feedback in a collaborative virtual environment
ACM Transactions on Computer-Human Interaction (TOCHI)
COLCOM '07 Proceedings of the 2007 International Conference on Collaborative Computing: Networking, Applications and Worksharing
Fiia: user-centered development of adaptive groupware systems
Proceedings of the 1st ACM SIGCHI symposium on Engineering interactive computing systems
It's about time: confronting latency in the development of groupware systems
Proceedings of the ACM 2011 conference on Computer supported cooperative work
Scheduling in variable-core collaborative systems
Proceedings of the ACM 2011 conference on Computer supported cooperative work
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Two important performance metrics in collaborative systems are local and remote response times. Previous analytical and simulation work has shown that these response times depend on three important factors: processing architecture, communication architecture, and scheduling of tasks dictated by these two architectures. We show that it is possible to create a system that improves response times by dynamically adjusting these three system parameters in response to changes to collaboration parameters such as new users joining and network delays changing. We present practical approaches for collecting collaboration parameters, computing multicast overlays, applying analytical models of previous work, preserving coupling semantics during optimizations, and keeping overheads low. Simulations and experiments show that the system improves performance in practical scenarios.