Replica Selection in Data Grids Using Preconditioning of Decision Attributes by K-means Clustering (K-RSDG)

This paper extends the applicability of the Rough Set Replica Selection Strategy in Data Grids, RSDG, proposed previously for such situations where the history of replica sites is unavailable. Grey based Rough Set Theory is applied using replicas information only as an input data. The Decision attributes are derived applying Grey based K-means clustering algorithm upon the input data. Each cluster label of K clusters represents a class of Decision attribute in the Decision Table of the rough set. Comparing to the previous work the synthetic data experimentation shows the improvement in the overall performance.