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CPU Load Predictions on the Computational Grid *

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3 Author(s)
Yuanyuan Zhang ; Japan Advanced Institute of Science and Technology, Japan ; Wei Sun ; Inoguchi, Y.

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.

Published in:

Cluster Computing and the Grid, 2006. CCGRID 06. Sixth IEEE International Symposium on  (Volume:1 )

Date of Conference:

16-19 May 2006

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