An approach to grid scheduling optimization based on fuzzy association rule mining

Author

Huang, Jin ; Jin, Hai ; Xie, Xia ; Zhang, Qin

Author_Institution

Cluster & Grid Comput. Lab, Huazhong Univ. of Sci. & Technol., Wuhan

fYear

2005

fDate

1-1 July 2005

Lastpage

195

Abstract

This paper presents a grid scheduling optimization technique based on knowledge discovery. The main idea is to transform the grid monitoring data into a performance data set, extract the association patterns of performance data through fuzzy association rule mining, then construct optimization logic according to the mining results, and finally optimize the grid scheduling. In the process of data mining, a method of association rule mining is proposed based on time-window and fuzzy set concepts, which can mine data for quantitative attribute value based on the attribute and time dimensions in grid performance data set

Keywords

data mining; fuzzy set theory; grid computing; scheduling; association patterns; data mining; fuzzy association rule mining; fuzzy sets; grid monitoring; grid scheduling optimization; knowledge discovery; optimization logic; quantitative attribute value; Association rules; Data mining; Delay; Dynamic scheduling; Fuzzy logic; Fuzzy sets; Grid computing; Monitoring; Processor scheduling; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

e-Science and Grid Computing, 2005. First International Conference on

Conference_Location

Melbourne, Vic.

Print_ISBN

0-7695-2448-6

Type

conf

DOI

10.1109/E-SCIENCE.2005.16

Filename

1572225