Enhancing Disk Drive Read Performance with Machine Learning: A Novel Approach Using Genetic Algorithms

As data storage demands continue to grow, optimizing disk drive read performance is crucial for enhancing system efficiency. This study introduces a novel approach leveraging machine learning techniques, particularly genetic algorithms, to improve disk drive read operations. By analyzing access patterns and dynamically optimizing read strategies, our method adapts to workload variations, reducing latency and improving overall performance. Experimental results demonstrate significant gains in read efficiency compared to traditional approaches, highlighting the potential of machine learning-driven optimization in modern storage systems.