Dynamic Data Replication and Job Scheduling Based on Popularity and Category
Dealing with a huge amount of data puts the requirement for efficient data access more critical in data grids. Improving data access time is a one way of reducing the job execution time i.e. improving performance. To speed up the data access and reduce bandwidth consumption, data grids replicate data in multiple locations. This paper studies a new data replication strategy in data grid, which takes into account two important issues concerning replication: storage capability of different nodes and bandwidth consumption between nodes. It also considers the popularity of the file for replacement. Lesser popular files get less priority then the higher popular file. The authors also need to consider the limitation on storage.