ABSTRACT OF THE DISSERTATION An Execution Context Optimization Framework for Disk Energy

Power, energy, and thermal concerns have had explosive growth in research over the past two decades. In servers, desktops, and mobile systems, the hard disk is among the top resources in power and energy consumption. Common techniques for reducing disk energy consumption have included caching, adaptive low power modes, batch scheduling, and data migration. Many previous software optimizations for sin-gle disk systems have assumed and experimented in uniprogramming environments. However, modern systems are typically multiprogramming, and the optimizations do not extend well from the uniprogramming model. Programs should be aware of con-currently running programs to enable cooperation and coordinate disk accesses from multiple programs. The set of concurrently running programs is referred to as an execution context. Execution context optimizations were introduced to target mul-tiprogramming environments. My research introduces an optimization framework to provide execution context information and reduce disk energy consumption by eectively managing disk accesses. Optimizing over all possible execution contexts is counter-productive becaus