Data Management Challenges of Data-Intensive Scientific Workflows
- 1 May 2008
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 33, 687-692
- https://doi.org/10.1109/ccgrid.2008.24
Abstract
Scientific workflows play an important role in today's science. Many disciplines rely on workflow technologies to orchestrate the execution of thousands of computational tasks. Much research to-date focuses on efficient, scalable, and robust workflow execution, especially in distributed environments. However, many challenges remain in the area of data management related to workflow creation, execution, and result management. In this paper we examine some of these issues in the context of the entire workflow lifecycle.Keywords
This publication has 18 references indexed in Scilit:
- Examining the Challenges of Scientific WorkflowsComputer, 2007
- Optimizing Workflow Data FootprintScientific Programming, 2007
- Scheduling Workflows with Budget ConstraintsPublished by Springer Nature ,2006
- Scheduling of scientific workflows in the ASKALON grid environmentACM SIGMOD Record, 2005
- Pegasus: A Framework for Mapping Complex Scientific Workflows onto Distributed SystemsScientific Programming, 2005
- Grid-based metadata servicesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Performance and scalability of a replica location servicePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Grid information services for distributed resource sharingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- The Anatomy of the Grid: Enabling Scalable Virtual OrganizationsThe International Journal of High Performance Computing Applications, 2001
- A worldwide flock of Condors: Load sharing among workstation clustersFuture Generation Computer Systems, 1996