Scientific Workflow Protocol Discovery from Public Event Logs in Clouds

With the advancement of cloud computing, many challenging scientific problems can be solved using scientific workflow technology which integrates geo-distributed instruments, applications, and big data effectively and efficiently. For workflow collaboration, the workflow protocols of all participants are needed. However, workflow protocols are not always available and are often outdated as the workflow evolve frequently. To address this problem, we propose a novel workflow discovery approach which can extract up-to-date scientific workflow protocols from public event logs in clouds, without the need to access the full-fledged event logs involving private events. Our approach leverages transitive precedence relations between events to achieve this. We implement our approach as a ProM plug-in, and evaluate it through extensive experiments on event logs of real-world scientific workflows. The experimental results demonstrate that our approach requires a weaker completeness notion of event logs than the state-of-the-art do, and our approach derives the same workflow protocol from the public event log as that discovered from the original event log, and thus the private events can be protected.