Computer Science Department
School of Computer Science, Carnegie Mellon University
The Case for Prediction-based Best-effort Real-time Systems
Peter A. Dinda, Bruce Lowekamp,
Loukas Kallivokas, David R. O'Hallaron
January 1999
A version of this paper appeared in the
Seventh Workshop on Parallel and Distributed Real-Time Systems (WPDDRTS'99)
CMU-CS-98-174.ps
CMU-CS-98-174.pdf
We propose a prediction-based best-effort real-time service to support
distributed, interactive applications in shared, unreserved computing
environments. These applications have timing requirements, but can
continue to function when deadlines are missed. In addition, they
expose two kinds of adaptability: tasks can be run on any host, and
their resource demands can be adjusted based on user-perceived
quality. After defining this class of applications, we describe two
significant examples, an earthquake visualization tool and a GIS map
display tool, and show how they could benefit from the service.
Finally, we present evidence that the service is feasible in the form
of two studies of algorithms for host load prediction and for
predictive task mapping.
18 pages
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