Performance of parallel I/O scheduling strategies on a network of workstations

Techniques for scheduling parallel I/O for both uniprogrammed systems that run single jobs in isolation and multiprogrammed environments that execute multiple parallel jobs simultaneously are presented. The performance of the scheduling algorithms is evaluated on a network of workstations. A new scheduling algorithm proposed in this paper is observed to perform very well for systems running single jobs in isolation. The algorithms that use knowledge of job characteristics are observed to produce a superior performance in multiprogrammed parallel environments.