Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning
Modern data-intensive applications demand efficient orchestration across heterogeneous storage tiers, ranging from high-performance DRAM to cost-effective cloud storage. Existing tiered storage systems predominantly employ reactive policies that respond to observed access patterns, leading to subopt...
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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/11072103/ |
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