This project addresses the challenges of successfully deploying large-scale parallel I/O servers to meet the demands of modern data-intensive applications multimedia retrieval, We and database servers, visualization and graphics, and spatial and temporal databases. The goals are to develop scheduling and resource management algorithms for parallel I/O systems, and increase our understanding of the complex underlying resource tradeoffs. These include basic scheduling issues dealing with parallel I/O, including those related to prefetching and caching, on -line scheduling, fair servicing of multiple users and deadline-constrained real-time parallel I/O. Secondly the algorithms designed in this research will be directly applied to areas like multimedia systems, including variable-bit rate (VBR) video retrieval, and Web, database and application servers dealing with large numbers of concurrent, interacting I/Os.
