Predicting Grid Resource Performance Online
Rich Wolski, Graziano Obertelli, Matthew S. Allen, Daniel Charles Nurmi, John Brevik · Kluwer Academic Publishers eBooks · 2006
In this chapter, we describe methods for predicting the performance of Computational Grid resources (machines, networks, storage systems, etc.) using computationally inexpensive statistical techniques. The predictions generated in this manner are intended to support adaptive application scheduling in Grid settings, as well as online fault detection. We describe a mixture-of-experts approach to nonparametric, univariate time-series forecasting, and detail the effectiveness of the approach using example data gathered from “production” (i.e., nonexperimental) Computational Grid installations.