PROJECT TITLE :

Binary-Tree Based Estimation of File Requests for Efficient Data Replication - 2017

ABSTRACT:

Recently, data replication has received considerable attention in the sphere of grid computing. The main goal of data replication algorithms is to optimize data access performance by replicating the most common files. When a file will not exist within the node where it had been requested, it necessarily must be transferred from another node, inflicting delays within the completion the file requests. The final plan behind information replication is to stay track of the foremost widespread files requested in the grid and produce copies of them in selected nodes. In this approach, more file requests will be completed over a amount of your time and average job execution time is reduced. In this paper, we tend to introduce an algorithm that estimates the potential of the files located in every node of the grid, using a binary tree structure. Conjointly, the file scope and also the file type are taken into consideration. By potential of a file, we tend to mean its increasing or decreasing demand over a amount of time. The file scope generally refers to the extent of the group of users that have an interest or probably fascinated by a file. The file types are divided into read and write intensive. Our scheme mainly promotes the high-potential files for replication, primarily based on the temporal locality principle. The simulation results indicate that the proposed theme will offer better knowledge access performance in terms of the hit ratio and the common job execution time, compared to other state-of-the-art strategies.