Modeling and Evaluation of SWAP Scheduling Policy Under Varying Job Size Distributions
Size-based scheduling policies have been shown to be effective resource allocation policies in computing and networked environments. One of the recently proposed size-based scheduling policy is called SWAP. It is a non-preemptive, threshold based policy that was proposed to approximate the Shortest Job First (SJF) policy by introducing service differentiation between short and large jobs such that short jobs are given service priority over the large jobs. Original study of the SWAP scheduling policy was based on only simulations, which are known to have a number of restrictions. In this paper, the authors derive SWAP models and evaluate the scheduling policy using workloads that have varying distributions.