Abstract
It is a complex task to design and implement a workflow management system that supports scalable executions of large-scale scientific workflows for dynamic and heterogeneous Grid environments. In this paper we describe the Distributed workflow Enactment Engine (DEE) of the ASKALON Grid application development environment for Grid computing. DEE proposes a de-centralized architecture that simplifies and reduces the overhead for managing large workflows through partitioning, improved data locality, and reduced workflow-level checkpointing overhead. We report experimental results for a real-world material science workflow application.
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