A Dataflow-Oriented Atomicity and Provenance System for Pipelined Scientific Workflows

Authors:
Liqiang Wang;Shiyong Lu;Xubo Fei;Jeffrey Ram
Affiliations:
Dept. of Computer Science, University of Wyoming, USA;Dept. of Computer Science, Wayne State University, USA;Dept. of Computer Science, Wayne State University, USA;Dept. of Physiology, Wayne State University, USA
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Year:
2007

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Abstract

Scientific workflows have gained great momentum in recent years due to their critical roles in e-Science and cyberinfrastructure applications. However, some tasks of a scientific workflow might fail during execution. A domain scientist might require a region of a scientific workflow to be "atomic". Data provenance, which determines the source data that are used to produce a data item, is also essential to scientific workflows. In this paper, we propose: (i) an architecture for scientific workflow management systems that supports both provenance and atomicity; (ii) a dataflow-oriented atomicity model that supports the notions of commit and abort; and (iii) a dataflow-oriented provenance model that, in addition to supporting existing provenance graphs and queries, also supports queries related to atomicity and failure.