Computing clouds became the platform of alternative for the preparation and execution of scientific workflows. owing to the uncertainty and unpredictability of scientific exploration, scientific workflows can't be absolutely specific at the modeling stage. it's so of nice significance to be able to discover actual workflows from the execution history (event logs) so as to breed experimental results and to ascertain place of origin. However, most existing method mining techniques target discovering management flow-oriented business processes during a centralized surroundings, thus, they're largely irrelevant to discovering information flow-oriented, unstructured scientific workflows in distributed cloud environments. during this paper, we gift SWMaaS (Scientific progress Mining as a Service) to support each intra-cloud and inter-cloud scientific progress mining. The approach is enforced as a promenade plug-in and is evaluated on event logs derived from real-world scientific workflows. Through experimental results, we demonstrate the effectiveness and potency of our approach.
Article Details
Unique Paper ID: 145607
Publication Volume & Issue: Volume 4, Issue 10
Page(s): 474 - 477
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