Resource Availability Prediction for Improved Grid Scheduling

Abstract

The frequent and volatile unavailability of volunteer-based grid computing resources challenges grid schedulers to make effective application placements. The manner in which host resources become unavailable will have different effects on different applications, depending on their runtime and their ability to be checkpointed or replicated. A multi-state availability model can help improve scheduling performance by capturing the various ways a resource may be available or unavailable to the grid. This paper uses a multi-state model and describes several prediction techniques to forecast resource transitions into the model's states. We analyze the accuracy of our predictors, which outperform existing approaches. Our approach increases the accuracy of multi-state resource availability prediction, and enables better application placement decisions that reduce the number of operations lost due to resource failure and eviction, decreases application makespan, or both.