A Provenance-Based Fault Tolerance Mechanism for Scientific Workflows

  • Authors:
  • Daniel Crawl;Ilkay Altintas

  • Affiliations:
  • San Diego Supercomputer Center, UCSD, La Jolla, USA CA 92093;San Diego Supercomputer Center, UCSD, La Jolla, USA CA 92093

  • Venue:
  • Provenance and Annotation of Data and Processes
  • Year:
  • 2008

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Abstract

Capturing provenance information in scientific workflows is not only useful for determining data-dependencies, but also for a wide range of queries including fault tolerance and usage statistics. As collaborative scientific workflow environments provide users with reusable shared workflows, collection and usage of provenance data in a generic way that could serve multiple data and computational models become vital. This paper presents a method for capturing data value- and control- dependencies for provenance information collection in the Kepler scientific workflow system. It also describes how the collected information based on these dependencies could be used for a fault tolerance framework in different models of computation.