Efficient hierarchical storage management empowered by reinforcement learning
With the rapid development of big data and cloud computing, data management has
become increasingly challenging. Over the years, a number of frameworks for data …
become increasingly challenging. Over the years, a number of frameworks for data …
Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract
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 …
become increasingly challenging. A possible solution is to use an intelligent hierarchical …
Efficient hierarchical storage management framework empowered by reinforcement learning
With the rapid development of big data and cloud computing, data management has
become increasingly challenging. Over the years, a number of frameworks for data …
become increasingly challenging. Over the years, a number of frameworks for data …
[HTML][HTML] Data management of scientific applications in a reinforcement learning-based hierarchical storage system
In many areas of data-driven science, large datasets are generated where the individual
data objects are images, matrices, or otherwise have a clear structure. However, these …
data objects are images, matrices, or otherwise have a clear structure. However, these …
A reinforcement learning framework for online data migration in hierarchical storage systems
D Vengerov - The Journal of Supercomputing, 2008 - Springer
Multi-tier storage systems are becoming more and more widespread in the industry. They
have more tunable parameters and built-in policies than traditional storage systems, and an …
have more tunable parameters and built-in policies than traditional storage systems, and an …
DHIS: discriminating hierarchical storage
A typical storage hierarchy comprises of components with varying performance and cost
characteristics, providing multiple options for data placement. We propose and evaluate a …
characteristics, providing multiple options for data placement. We propose and evaluate a …
[PDF][PDF] Dynamic tuning of online data migration policies in hierarchical storage systems using reinforcement learning
D Vengerov - 2006 - Citeseer
Multi-tier storage systems are becoming more and more widespread in the industry. In order
to minimize the request response time in such systems, the most frequently accessed (“hot”) …
to minimize the request response time in such systems, the most frequently accessed (“hot”) …
Optimizing data placement on hierarchical storage architecture via machine learning
P Cheng, Y Lu, Y Du, Z Chen, Y Liu - … 2019, Hohhot, China, August 23–24 …, 2019 - Springer
As storage hierarchies are getting deeper on modern high-performance computing systems,
intelligent data placement strategies that can choose the optimal storage tier dynamically is …
intelligent data placement strategies that can choose the optimal storage tier dynamically is …
Machine learning for data management: A system view
Machine learning techniques have been proposed to optimize data management in recent
years. Compared with traditional empirical data management, learning-based methods …
years. Compared with traditional empirical data management, learning-based methods …
hStorage-DB: Heterogeneity-aware data management to exploit the full capability of hybrid storage systems
As storage systems become increasingly heterogeneous and complex, it adds burdens on
DBAs, causing suboptimal performance even after a lot of human efforts have been made. In …
DBAs, causing suboptimal performance even after a lot of human efforts have been made. In …