Lexicographic QoS scheduling for parallel I/O

High-end shared storage systems serving multiple independent workloads must assure that concurrently executing clients will receive a fair or agreed-upon share of system I/O resources. In a parallel I/O system an application makes requests for specific disks at different steps of its computation depending on the data layout and its computational state. Different applications contend for disk access making the problem of maintaining fair allocation challenging.We propose a model for differentiated disk bandwidth allocation based on lexicographic minimization, and provide new efficient scheduling algorithms to allocate the I/O bandwidth fairly among contending applications. A major contribution of our model is its ability to handle multiple parallel disks and contention for disks among the concurrent applications. Analysis and simulation-based evaluation shows that our algorithms provide performance isolation, weighted allocation of resources, and are work conserving. The solutions are also applicable to other shared resource environments dealing with non-uniform heterogeneous servers.