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.
@article{arxiv.2512.07280,
title = {ContinuumConductor : Decentralized Process Mining on the Edge-Cloud Continuum},
author = {Hendrik Reiter and Janick Edinger and Martin Kabierski and Agnes Koschmider and Olaf Landsiedel and Arvid Lepsien and Xixi Lu and Andrea Marrella and Estefania Serral and Stefan Schulte and Florian Tschorsch and Matthias Weidlich and Wilhelm Hasselbring},
journal= {arXiv preprint arXiv:2512.07280},
year = {2025}
}