A Provenance-based Adaptive Scheduling Heuristic for Parallel Scientific Workflows in Clouds
Journal of Grid Computing
Capturing and querying workflow runtime provenance with PROV: a practical approach
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Scheduling parameter sweep workflow in the Grid based on resource competition
Future Generation Computer Systems
The analysis of service provider-user coordination for resource allocation in cloud computing
Information-Knowledge-Systems Management
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Most existing workflow scheduling algorithms only consider a computing environment in which the number of compute resources is bounded. Compute resources in such an environment usually cannot be provisioned or released on demand of the size of a workflow, and these resources are not released to the environment until an execution of the workflow completes. To address the problem, we firstly formalize a model of a Cloud environment and a workflow graph representation for such an environment. Then, we propose the SHEFT workflow scheduling algorithm to schedule a workflow elastically on a Cloud computing environment. Our preliminary experiments show that SHEFT not only outperforms several representative workflow scheduling algorithms in optimizing workflow execution time, but also enables resources to scale elastically at runtime.