Reiter, HendrikHendrikReiterEdinger, JanickJanickEdingerKabierski, MartinMartinKabierskiKoschmider, AgnesAgnesKoschmiderLandsiedel, OlafOlafLandsiedelLepsien, ArvidArvidLepsienLu, XixiXixiLuMarrella, AndreaAndreaMarrellaSerral, EstefaniaEstefaniaSerralSchulte, StefanStefanSchulteTschorsch, FlorianFlorianTschorschWeidlich, MatthiasMatthiasWeidlichHasselbring, WilhelmWilhelmHasselbring2026-01-222026-01-222025-12-08arXiv: 2512.07280v1 (2025)https://hdl.handle.net/11420/60967Process 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.enhttps://creativecommons.org/licenses/by/4.0/cs.DCComputer Science, Information and General Works::005: Computer Programming, Programs, Data and Security::005.7: DataComputer Science, Information and General Works::006: Special computer methods::006.3: Artificial IntelligenceComputer Science, Information and General Works::004: Computer SciencesPreprinthttps://doi.org/10.15480/882.1650610.48550/arXiv.2512.0728010.15480/882.165062512.07280v1Preprint