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ContinuumConductor: Decentralized process mining on the edge-cloud continuum
Citation Link: https://doi.org/10.15480/882.16506
Publikationstyp
Preprint
Date Issued
2025-12-08
Sprache
English
TORE-DOI
Citation
arXiv: 2512.07280v1 (2025)
Publisher DOI
ArXiv ID
Peer Reviewed
false
Process mining traditionally assumes centralized event data collection and analysis. However, modern Industrial Internet of Things systems increasingly operate over distributed, resource-constrained edge-cloud infrastructures. This paper proposes a structured approach for decentralizing process mining by enabling event data to be mined directly within the IoT systems edge-cloud continuum. We introduce ContinuumConductor a layered decision framework that guides when to perform process mining tasks such as preprocessing, correlation, and discovery centrally or decentrally. Thus, enabling privacy, responsive and resource-efficient process mining. For each step in the process mining pipeline, we analyze the trade-offs of decentralization versus centralization across these layers and propose decision criteria. We demonstrate ContinuumConductor at a real-world use-case of process optimazition in inland ports. Our contributions lay the foundation for computing-aware process mining in cyber-physical and IIoT systems.
Subjects
cs.DC
DDC Class
005.7: Data
006.3: Artificial Intelligence
004: Computer Sciences
Publication version
publishedVersion
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Name
2025_Reiter_ContinuumConductor_DecentralizedProcessMiningOnTheEdgeCloudContinuum.pdf
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