A Replica Selection Approach based on Prediction in Data Grid

Data replication is adopted to improve data access performance in data grid. When different sites hold replicas, there are significant benefits while selecting the best replica. In this paper, we propose a new replica selection algorithm based on prediction. Analyzing the factors infecting replica selection, The grey system theory is utilized to help predicting the data response time on the basis the GM(1,1) grey dynamic model; Meanwhile the Markov chain is applied to achieve state transition probability matrix to predict the reliability of replicas in the form of probability by the system state classification. The simulation results show that in our replica selection model, the prediction is valid, helpful to selection decision, and is able to achieve load balance between nodes holding replicas.