Study on Distributed Clustering Analysis Processing Strategy Based on P2P in EFCS-Grid
Data visualization by means of data mining is an effective method for presenting an amount of data to users. In EFCS-Grid, data are clustered by using k-mean based on given attributes, then to present the result to users. This paper tests and analyzes the time cost of data clustering analysis implementing at centralized server in case of multi-users, and the total time cost of data processing in EFCS-Grid in different conditions, and draw an conclusion that the time cost of data clustering analysis is more important in that of data process in EFCS-Grid, and the performance of the grid system will become lower greatly with the data amount processed increasing. Thus a distributed clustering analysis strategy is proposed by means of P2P structure, in which data integration layer and data clustering layer are included, the former one integrates the partial data into a complete schema on users demand,then to implement two times data clustering analysis to reach the purposes of easing the deficiency of centralized clustering analysis and improving the efficiency of data clustering by using the distributed computing capability of P2P structure.