Slot Selection Algorithms for Economic Scheduling in Distributed Computing with High QoS Rates

Abstract

In this work, we address the problem of slot selection and co-allocation for parallel jobs in distributed computing with non-dedicated resources. A single slot is a time span that can be assigned to a task, which is a part of a job. The job launch requires a co-allocation of a specified number of slots starting synchronously. The challenge is that slots associated with different CPU nodes of distributed computational environments may have arbitrary start and finish points that do not match. Some existing algorithms assigns 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 of linear complexity are studied and compared with known decisions. The proposed algorithms allow overall increase in the quality of service (QoS) for each of the considered rates: job start time, finish time, runtime, CPU usage time and total cost of job execution.