Storage System

Modern storage systems face challenges in managing performance and reliability amidst increasing data volumes and diverse hardware. Current research focuses on leveraging machine learning, particularly reinforcement learning, to optimize data placement, cache management, and resource allocation in hybrid and puzzle-based storage architectures. These techniques aim to improve system predictability, reduce latency, and enhance throughput, addressing critical issues in cloud computing and data center operations. The resulting improvements in efficiency and reliability have significant implications for both the performance of large-scale data systems and the development of advanced storage technologies.