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Pegasus: A framework for mapping complex scientific workflows onto distributed systems
The results of improving application performance through workflow restructuring which clusters multiple tasks in a workflow into single entities are presented.
The Open Provenance Model core specification (v1.1)
PROV-DM: The PROV Data Model
This document introduces the provenance concepts found in PROV and defines PROV-DM types and relations.
A survey of trust in computer science and the Semantic Web
Pegasus: Mapping Scientific Workflows onto the Grid
- E. Deelman, J. Blythe, M. Livny
- Computer Science, PhysicsEuropean Across Grids Conference
- 28 January 2004
The Pegasus system that can map complex workflows onto the Grid and takes an abstract description of a workflow and finds the appropriate data and Grid resources to execute the workflow is described.
Mapping Abstract Complex Workflows onto Grid Environments
The current ACWG based on AI planning technologies is described and it is outlined how these technologies can play a crucial role in developing complex application workflows in Grid environments.
Examining the Challenges of Scientific Workflows
A recent National Science Foundation workshop brought together domain, computer, and social scientists to discuss requirements of future scientific applications and the challenges they present to current workflow technologies.
The Cognitive Atlas: Toward a Knowledge Foundation for Cognitive Neuroscience
A new open collaborative project is described that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas, and how this project has the potential to drive novel discoveries about both mind and brain.
Task scheduling strategies for workflow-based applications in grids
- J. Blythe, S. Jain, K. Kennedy
- Computer ScienceCCGrid . IEEE International Symposium on Cluster…
- 9 May 2005
This work identifies two families of resource allocation algorithms: task-based algorithms that greedily allocate tasks to resources, and workflow- based algorithms that search for an efficient allocation for the entire workflow.
PRODIGY: an integrated architecture for planning and learning
The PRODIGY architecture is described, describing its planning and problem solving capabilities and touching upon its multiple learning methods, as well as issues in architectural design, providing a context to examine the underlying tenets of the PRODigY architecture.