Abstract: A multi-tier scheduling approach includes a first tier comprising virtual cluster allocators that receive scheduling requests from processes and aggregate those requests and provide them to a second tier, namely a single resource distributor for the entire set of computing devices. The resource distributor, based on the requests from virtual cluster allocators, and also from information received from the computing devices themselves, generates a flow graph to identify an optimal scheduling of the assignment of resources to specific ones of the virtual clusters. Each virtual cluster allocator then, based on the assignment of resources assigned to it by the resource distributor, solves its own flow graph to identify an optimal scheduling of processes on the resources assigned.

Abstract: A computing cluster operated according to a resource allocation policy based on a predictive model of completion time. The predictive model may be applied in a resource control loop that iteratively updates resources assigned to an executing job. At each iteration, the amount of resources allocated to the job may be updated based on of the predictive model so that the job will be scheduled to complete execution at a target completion time. The target completion time may be derived from a utility function determined for the job. The utility function, in turn, may be derived from a service level agreement with service guarantees and penalties for late completion of a job. Allocating resources in this way may maximize utility for an operator of the computing cluster while minimizing disruption to other jobs that may be concurrently executing.

Abstract: A multi-tier scheduling approach includes a first tier comprising virtual cluster allocators that receive scheduling requests from processes and aggregate those requests and provide them to a second tier, namely a single resource distributor for the entire set of computing devices. The resource distributor, based on the requests from virtual cluster allocators, and also from information received from the computing devices themselves, generates a flow graph to identify an optimal scheduling of the assignment of resources to specific ones of the virtual clusters. Each virtual cluster allocator then, based on the assignment of resources assigned to it by the resource distributor, solves its own flow graph to identify an optimal scheduling of processes on the resources assigned.