CPU Load Predictions on the Computational Grid*This research is conducted as a program for the "21st Century COE Program" by Ministry of Education, Culture, Sports, Science and Technology, Japan.

  • Authors:

  • Yuanyuan Zhang;Wei Sun;Yasushi Inoguchi

  • Affiliations:

  • The authors are with the Graduate School of Information Science, JAIST, Nomi-shi, 923--1292 Japan. E-mail: yuanyuan@jaist.ac.jp,;The authors are with the Graduate School of Information Science, JAIST, Nomi-shi, 923--1292 Japan. E-mail: yuanyuan@jaist.ac.jp,;The author is with the Center for Information Science, JAIST and PREST, Japan Science and Technology Agency, Nomi-shi, 923--1292 Japan.,

  • Venue:
  • IEICE - Transactions on Information and Systems
  • Year:
  • 2007

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Abstract

To make the best use of the resources in a shared grid environment, an application scheduler must make a prediction of available performance on each resource. In this paper, we examine the problem of predicting available CPU performance in time-shared grid system. We present and evaluate a new and innovative method to predict the one-step-ahead CPU load in a grid. Our prediction strategy forecasts the future CPU load based on the variety tendency in several past steps and in previous similar patterns, and uses a polynomial fitting method. Our experimental results on large load traces collected from four different kinds of machines demonstrate that this new prediction strategy achieves average prediction errors which are between 22% and 86% less than those incurred by four previous methods.