Scheduling Data-IntensiveWorkflows onto Storage-Constrained Distributed Resources

@article{Ramakrishnan2007SchedulingDO,
  title={Scheduling Data-IntensiveWorkflows onto Storage-Constrained Distributed Resources},
  author={Arun Ramakrishnan and Gurmeet Singh and Henan Zhao and Ewa Deelman and Rizos Sakellariou and Karan Vahi and Kent Blackburn and David Meyers and Michael Samidi},
  journal={Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)},
  year={2007},
  pages={401-409}
}
In this paper we examine the issue of optimizing disk usage and of scheduling large-scale scientific workflows onto distributed resources where the workflows are data- intensive, requiring large amounts of data storage, and where the resources have limited storage resources. Our approach is two-fold: we minimize the amount of space a workflow requires during execution by removing data files at runtime when they are no longer required and we schedule the workflows in a way that assures that the… CONTINUE READING
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