A Multi-criteria Class-based Job Scheduler for Large Computing Farms

In this paper we propose a new multi-criteria class-based job scheduler able to dynamically schedule a stream of batch jobs on large-scale computing farms. It is driven by several configuration parameters allowing the scheduler customization with respect to the goals of an installation. The proposed scheduling policies allow to maximize the resource usage and to guarantee the applications QoS requirements. The proposed solution has been evaluated by simulations using different streams of synthetically generated jobs. To analyze the quality of our solution we propose a new methodology to estimate whether at a given time the resources in the system are really sufficient to meet the service level requested by the submitted jobs. Moreover, the proposed solution was also evaluated comparing it with the Backfilling and Flexible backfilling algorithms. Our scheduler demonstrated to be able to carry out good scheduling choices.