Distributed and Parallel Databases
A taxonomy of scientific workflow systems for grid computing
ACM SIGMOD Record
Enabling ScientificWorkflow Reuse through Structured Composition of Dataflow and Control-Flow
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
VisTrails: visualization meets data management
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Scientific workflow management and the Kepler system: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Programming scientific and distributed workflow with Triana services: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Dynamic Workflow Control with Global States Monitoring
ISPDC '07 Proceedings of the Sixth International Symposium on Parallel and Distributed Computing
Tackling the Provenance Challenge one layer at a time
Concurrency and Computation: Practice & Experience - The First Provenance Challenge
A Lightweight Middleware Monitor for Distributed Scientific Workflows
CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
Provenance for Computational Tasks: A Survey
Computing in Science and Engineering
Composing Different Models of Computation in Kepler and Ptolemy II
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
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Distributing workflow tasks among high performance environments involves local processing and remote execution on clusters and grids. This dis-tribution often needs interoperation between heterogeneous workflow definition languages and their corresponding execution machines. A centralized Workflow Management System (WfMS) can be locally controlling the execution of a workflow that needs a grid WfMS to execute a sub-workflow that requires high performance. Workflow specification languages often provide different control-flow execution structures. Moving from one environment to another requires mappings between these languages. Due to heterogeneity, control-flow structures, available in one system, may not be supported in another. In these heterogeneous distributed environments, provenance gathering becomes also heterogeneous. This work presents control-flow modules that aim to be independent from WfMS. By inserting these control-flow modules on the workflow specification, the workflow execution control becomes less dependent of heterogeneous workflow execution engines. In addition, they can be used to gather provenance data both from local and remote execution, thus allowing the same provenance registration on both environments independent of the heterogeneous WfMS. The proposed modules extend the ordinary workflow tasks by providing dynamic behavioral execution control. They were implemented in the VisTrails graphical workflow enactment engine, which offers a flexible infrastructure for provenance gathering.