HCC: Evaluating the Performance of Distributed Synchronous Collaboration Architectures

There has been a recent proliferation of industrial-strength synchronous collaborative systems, however, there has been little research comparing the performance of their distributed architectures, even though inadequate performance can be a show-stopper. In systematically examining this architectural design space, this project will provide a critical foundation for what is currently the ''black art'' of collaborative system design. This will have broad ranging impact in both research and industry.

The architecture design space will be modeled by several architecture parameters (e.g., transport protocol, server configuration, I/O scheduling), system parameters (e.g., network latency, processing power) and task parameters (e.g., I/O size, think time) that impact performance. Equations will be developed that give the value of the time, along key metrics such as join, leave, response, feedthrough, and task-completion, as a function of the architecture, system, and task parameters. Experiments will be performed to validate these equations using logs of different kinds of collaborations such as multi-user presentations, chats, and scientific visualizations. This novel experimental test bed will enable performance comparisons that have not been possible before.

Broader impact: The analytic model resulting from this research will allow application and infrastructure developers to determine the range of architectures they should implement. It will provide scientists, engineers, writers, and other users of collaboration technology a better understanding of the design space so they can choose the correct architecture to fit their needs while appreciating the performance consequences of that choice. In addition, the project infrastructure will form the first proof-of-concept system supporting the entire space of collaborative architectures, a novel research test-bed for experimentation, and a vehicle for teaching collaboration architectures. The multi-user activity logs created for these experiments will be publicized so that they can become benchmarks, in both academic and industrial research, used to compare performance of new architectures.