Matching application access patterns to storage device characteristics

Conventional computer systems have insufficient information about storage device performance characteristics. As a consequence, they utilize the available device resources inefficiently, which, in turn, results in poor application performance. This dissertation demonstrates that a few high-level, device-independent hints encapsulating unique storage device characteristics can achieve significant I/O performance gains without breaking the established abstraction of a storage device as a linear address space of fixed-size blocks. A piece of system software (here referred to as storage manager), which translates application requests into individual I/Os, can automatically match application access patterns to the provided characteristics. This results in more efficient utilization of storage devices and thus improved application performance. This dissertation (i) identifies specific features of disk drives, disk arrays, and MEMS-based storage devices not exploited by conventional systems, (ii) quantifies the potential performance gains these features offer, and (iii) demonstrates on thre