Optimization of Resources Selection for Jobs Scheduling in Heterogeneous Distributed Computing Environments

In this work, we introduce slot selection and co-allocation algorithms for parallel jobs in distributed computing with non-dedicated and heterogeneous resources (clusters, CPU nodes equipped with multicore processors, networks etc.). A single slot is a time span that can be assigned to a task, which is a part of a parallel job. The job launch requires a co-allocation of a specified number of slots starting and finishing synchronously. The challenge is that slots associated with different heterogeneous resources of distributed computing environments may have arbitrary start and finish points, different pricing policies. Some existing algorithms assign a job to the first set of slots matching the resource request without any optimization (the first fit type), while other algorithms are based on an exhaustive search. In this paper, algorithms for effective slot selection are studied and compared with known approaches. The novelty of the proposed approach is in a general algorithm selecting a set of slots efficient according to the specified criterion.