OSG Document 542-v1

Scheduling Data-Intensive Workflows onto Storage-Constrained Distributed Resources

Document #:
Document type:
Scentific Journal/Publications
Submitted by:
Marcia Teckenbrock
Updated by:
Marcia Teckenbrock
Document Created:
09 Feb 2007, 11:02
Contents Revised:
09 Feb 2007, 11:02
Metadata Revised:
09 Feb 2007, 11:02
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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 dataintensive,
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 amount of
data required and generated by the workflow fits onto the
individual resources. For a workflow used by gravitationalwave
physicists, we were able to improve the amount of
storage required by the workflow by up to 57%. We also
designed an algorithm that can not only find feasible solutions
for workflow task assignment to resources in diskspace
constrained environments, but can also improve the
overall workflow performance.
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Published in the Seventh IEEE International Symposium on Cluster Computing and the Grid — CCGrid 2007.
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