The Case for Prediction-Based Best-Effort Real-Time Systems

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 a significant example, an earthquake visualization tool, and show how it 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.

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