Proactive and Adaptive Data Migration in Hierarchical Storage Systems Using Reinforcement Learning Agent

Provided by: International Journal of Computer Applications
Topic: Storage
Format: PDF
With the data generation rates growing exponentially, businesses are having a difficult time maintaining data center infrastructure. Hierarchical storage systems has evolved as a better alternate to managing data, as frequently accessed data is placed on higher tiers and the least frequently accessed data on lower tiers. But the data arrangement is not always static. Data migration is an operation in which the selected data is physically moved, or migrated, to different storage components. The existing method of data migration in hierarchical storage systems has several shortcomings - reactive, heuristic policies and proprietary software.

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