Software Engineering White Papers
An Investigation of Grid Performance Predictions Through Statistical Learning
Overview Scheduling in large scale distributed systems like Grids is challenging because of their dynamics, heterogeneity, and lack of central control. In such environments performance predictions play an important role on providing input information required by a Grid scheduler. This paper investigates a set of statistical learning techniques in predicting two performance metrics in the Grid, namely, application run time and queue wait time on space-shared computing resources. This paper proposes Instance Based Learning (IBL) as a common framework to predict both metrics, with the IBL parameters optimized by genetic search.
| Publisher | Leiden University | File Format | |
|---|---|---|---|
| Date Published | April 2006 | ||
| Format | White Papers | ||
| Topics | |||
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