An innovative replica consistency decision model with Naive Bayesian Classifier in data grids
Jih‐Sheng Chang, Ruay-Shiung Chang · Journal of the Chinese Institute of Engineers · 2008
Data grid is one of the most popular applications in grid computing. In data grids, replication is a critical technology aiming at lowering the access delay as well as saving network bandwidth by duplicating original data in a distributed manner. Files were considered read‐only in most of the previous research work about data replication. For read/write files, replica consistency is an important issue. In this paper, we propose a novel replica consistency decision model with high adaptability and flexibility using the Naive Bayesian Classifier in order to improve the system performance in data grids. A system prototype has been implemented. The experimental results also prove the excellence of the proposed model.