Title :
Rough Set-based Intelligent Agent Grid Data Management
Author :
Chen, Jia ; Liu, Di
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
This paper proposed an intelligent agent grid data management method based on rough set. It can effectively classify data based on attributes reduction in rough set. After obtaining the classified data sets, it dispatches a collection of agents to coordinate a user job over grid computing to process the certain data sets. Our method can well resolve the main problems exist in grid data management. The experimental results indicates our proposed approach can reduce about sixteen percent implement time comparing to general grid data management without rough set classification.
Keywords :
data handling; grid computing; pattern classification; rough set theory; software agents; data classification; grid computing; intelligent agent grid data management; rough classified data sets; rough set classification; Collaboration; Computer science; Databases; Grid computing; Information systems; Intelligent agent; Large-scale systems; Paper technology; Set theory; Technology management;
Conference_Titel :
Communications, Circuits and Systems, 2007. ICCCAS 2007. International Conference on
Conference_Location :
Kokura
Print_ISBN :
978-1-4244-1473-4
DOI :
10.1109/ICCCAS.2007.4348202
