Scientific Workflow Protocol Discovery from Public Event Logs in Clouds

Wei Song, Hans Arno Jacobsen, Fangfei Chen

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

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 However, workflow protocols are not always available and are often outdated as the workflow evolve frequently.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.

Original languageEnglish
Article number8734698
Pages (from-to)2453-2466
Number of pages14
JournalIEEE Transactions on Knowledge and Data Engineering
Volume32
Issue number12
DOIs
StatePublished - 1 Dec 2020

Keywords

  • Scientific workflow
  • event log
  • privacy preservation
  • process discovery
  • transitive precedence
  • workflow protocol

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