Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract.
IEEE Transactions on Knowledge and Data Engineering(2023)
摘要
With the rapid development of big data and cloud computing, data management has become increasingly challenging. A possible solution is to use an intelligent hierarchical (multi-tier) storage system (HSS). An HSS is a meta solution that consists of different storage frameworks organized as a jointly constructed storage pool. A built-in data migration policy that determines the optimal placement of the datasets in the hierarchy is essential. Placement decisions are a non-trivial task since they should be made according to the characteristics of the dataset, the tier status in a hierarchy, and access patterns. This paper presents an open-source hierarchical storage framework with a dynamic migration policy based on reinforcement learning (RL).
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关键词
Data management,cloud computing,hierarchical storage system,data migration,reinforcement learning
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