Partitioning and scheduling workflows across multiple sites with storage constraints

Abstract

This paper aims to address the problem of scheduling large workflows onto multiple execution sites with storage constraints. Three heuristics are proposed to first partition the workflow into sub-workflows. Three estimators and two schedulers are then used to schedule sub-workflows to the execution sites. Performance with three real-world workflows shows that this approach is able to satisfy storage constraints and improve the overall runtime by up to 48% over a default whole-workflow scheduling. © 2012 Springer-Verlag.