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Supporting large-scale scientific workflows in distributed network environments and optimizing their performances are crucial to the success of collaborative scientific discovery. We develop a generic scientific workflow platform, referred to as SciFlow, which constitutes a flexible framework to facilitate the distributed execution and management of scientific workflows and incorporates a class of...
Many large-scale scientific applications feature distributed computing workflows of complex structures that must be executed and transferred in shared wide-area networks consisting of unreliable nodes and links. Mapping these computing workflows in such faulty network environments for optimal latency while ensuring certain fault tolerance is crucial to the success of eScience that requires both performance...
Large-scale data-intensive streaming applications in various science fields feature complex DAG-structured workflows comprised of distributed computing modules with intricate inter-module dependencies. Supporting such workflows in high-performance network environments and optimizing their throughput are crucial to collaborative scientific exploration and discovery. We formulate workflow mapping as...
Large-scale computation-intensive applications in various science fields feature complex DAG-structured workflows comprised of distributed computing modules with intricate inter-module dependencies. Supporting such workflows in heterogeneous network environments and optimizing their end-to-end performance are crucial to the success of large-scale collaborative scientific applications. We design and...
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