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

Identifieur interne : 000219 ( Istex/Corpus ); précédent : 000218; suivant : 000220

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

Auteurs : Liqiang Wang ; Shiyong Lu ; Xubo Fei ; Jeffrey Ram

Source :

RBID : ISTEX:48AE9890FC65C1CD833AEF9852CE22227CD35F7D

Abstract

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.

Url:
DOI: 10.1007/978-3-540-72588-6_42

Links to Exploration step

ISTEX:48AE9890FC65C1CD833AEF9852CE22227CD35F7D

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<Para>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: (
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) a dataflow-oriented atomicity model that supports the notions of commit and abort; and (
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<abstract lang="en">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.</abstract>
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