Dynamic Data Storage and Replication Based on the Category and Data Access Patterns

Abstract: Now days, Big data storage is becoming tricky issue. And it’s becoming current popular research topic. Dealing with the large scale massive data needed to be stored efficiently and accessed easily which is a crucial problem. This paper gives the solution to this problem. Category wise Data distribution will help to improve the data access time. And ultimately it will reduce the job execution time which will improve in the performance of data grid. Here we are using one algorithm K-Means to divide the data category wise. Then we are working on the limited storage capacity of the node. Due to limited capacity of the node we need to replace the data and to do this we need some replication strategy. So here we are using different Strategy depending on the user’s data access pattern. This paper will focus on the improvement of the performance, reduction in bandwidth consumption, Efficient and easy data access.