The Community for Technology Leaders
Cluster Computing and the Grid, IEEE International Symposium on (2006)
May 16, 2006 to May 19, 2006
ISBN: 0-7695-2585-7
pp: 321-326
The ability to accurately predict future resource capabilities is of great importance for applications and scheduling algorithms which need to determine how to use time-shared resources in a dynamic grid environment. In this paper we present and evaluate a new and innovative method to predict the one-stepahead CPU load in a grid. Our prediction strategy forecasts the future CPU load based on the tendency in several past steps and in previous similar patterns, and uses a polynomial fitting method. Our experimental results demonstrate that this new prediction strategy achieves average prediction errors that are between 37% and 86% lower than those incurred by the previously best tendency-based method.
Grid computing, Information science, Polynomials, Processor scheduling, Time series analysis, Sun, Scheduling algorithm, Load forecasting, Internet, Aggregates

"CPU Load Predictions on the Computational Grid *," Cluster Computing and the Grid, IEEE International Symposium on(CCGRID), Singapore, 2013, pp. 321-326.
98 ms
(Ver 3.3 (11022016))