Dynamic Work.ow in a Grid Enabled Problem Solving Environment

In a problem solving environment (PSE), a scientific workflow management system (SWMS) provides a meta environment for managing activities and data in scientific experiments, for prototyping experimental computing systems and for orchestrating the runtime system behaviour. A grid infrastructure makes data and computing intensive experiments feasible in PSEs but also requires the management of workflow to support dynamics of the flow execution. A dynamic SWMS includes a human user in the runtime loop of a flow execution, and allows an engine to flexibly orchestrate a workflow according to the human decision and the runtime states of the environment. In this paper, we present our research in an ongoing project: virtual laboratory for e-Science (VL-e). An agent based solution is proposed to enhance an existing grid enabled problem solving environment framework called VLAM-G. The intelligence for problem solving strategies and for workflow orchestration is encapsulated as knowledge in two types of agents: study managers and scenario conductors

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