Networks of workstations (NOWs) have been emerged as a primary infrastructure for scientific computing. NOWS are currently used to provide desktop sequential computing and visualization, high throughput opportunistic computing of batched sequential jobs, and dedicated parallel computing. In addition, we envision NOWs being used to store and retrieve data sets using scientific database management systems (DBMSs), provide opportunistic computation of parallel programs, allow interactive visualization of large disk resident data sets. The current state of knowledge provides most of the tools to enable this envisioned NOW usage, but lacks the needed scheduling policies. To remedy this, this project will: * Devise new scheduling algorithms to handle mixed workloads of workstations jobs, batched opportunistic sequential jobs, and batched opportunistic parallel jobs. * Characterize scientific DBMS workloads and develop designs on how best to integrate scientific DBMSs into the NOW. * Determine how best to integrate indexing techniques to provide support for interactive visualization of large disk resident data sets. * Develop system wide scheduling policies that are cognizant of all aspects of NOW usage. The goal of such policies is to provide good aggregate performance of all concurrently running applications including computation, visualization, and data access. The proposed work will develop comprehensive analytical and simulation models of NOW performance, including all of the above factors, to determine how to optimize overall performance and will develop a working prototype of the system.
