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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/7868

Title: Predict task running time in grid environments based on CPU load predictions
Authors: Zhang, Yuanyuan
Sun, Wei
Inoguchi, Yasushi
Keywords: Grid
task
running time prediction
Polynomial fitting
pattern
Issue Date: 2008-06
Publisher: Elsevier
Magazine name: Future Generation Computer Systems
Volume: 24
Number: 6
Start page: 489
End page: 497
DOI: 10.1016/j.future.2007.07.003
Abstract: A good running time prediction of tasks is very helpful and important for job scheduling and resource management of Grid. In this paper we present a running time prediction method for Grid tasks based on our previous work, which is a novel CPU load prediction method. In order to eliminate the interference of other factors, such as the memory accessing, network performance, and fluctuation of CPU processing capacity and so on, we produce a simulation to test and evaluate our prediction method. In this simulation we use more than 10,000 randomized test cases run on load traces sampled from 39 different machines. The simulation results are excellent and demonstrate that our running time prediction of Grid tasks outperforms significantly that of a widely existing prediction method.
Rights: NOTICE: This is the author’s version of a work accepted for publication by Elsevier. Changes resulting from the publishing process, including peer review, editing, corrections, structural formatting and other quality control mechanisms, may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Yuanyuan Zhang, Wei Sun, Yasushi Inoguchi, Future Generation Computer Systems, 24(6), 2008, 489-497, http://dx.doi.org/10.1016/j.future.2007.07.003
URI: http://hdl.handle.net/10119/7868
Material Type: author
Appears in Collections:e10-1. 雑誌掲載論文 (Journal Articles)

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