Rough Set-based Intelligent Agent Grid Data Management
Jia Chen, Di Liu · 2007
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.