Data Placement

Data placement optimizes the location of data across storage systems to maximize performance and efficiency. Current research focuses on developing adaptive and distributed algorithms, such as reinforcement learning and game-theoretic approaches (e.g., auctions and Glauber dynamics), to address the challenges of non-metric data placement in diverse environments like hybrid storage systems. These advancements aim to improve performance significantly, reduce the complexity of system design, and enable efficient resource utilization in increasingly complex storage architectures.