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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/o2ooqcbwafg45e546duritbwjy" style="color: black;">2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery</a>
Cloud computing is gaining tremendous momentum in both academia and industry. The application of Cloud computing, however, has mostly focused on Web applications and business applications; while the recognition of using Cloud computing to support large-scale workflows, especially dataintensive scientific workflows on the Cloud is still largely overlooked. We coin the term "Cloud Workflow", to refer to the specification, execution, provenance tracking of large-scale scientific workflows, as well<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cyberc.2011.80">doi:10.1109/cyberc.2011.80</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cyberc/ZhaoFRL11.html">dblp:conf/cyberc/ZhaoFRL11</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zlpe7p73lnh2jksgtnstvkafn4">fatcat:zlpe7p73lnh2jksgtnstvkafn4</a> </span>
more »... as the management of data and computing resources to enable the execution of scientific workflows on the Cloud. In this paper, we analyze why there has been such a gap between the two technologies, and what it means to bring Cloud and workflow together; we then present the key challenges in running Cloud workflow, and discuss the research opportunities in realizing workflows on the Cloud. Cloud computing; Scientific Workflow; Cloud workflow; Data Intensive Computing I.
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