most citedContinuumConductor : Decentralized Process Mining on the Edge-Cloud Continuum

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.DC20251 cited

ContinuumConductor : Decentralized Process Mining on the Edge-Cloud Continuum

Hendrik Reiter, Janick Edinger, Martin Kabierski +10

Process mining traditionally assumes centralized event data collection and analysis. However, modern Industrial Internet of Things systems increasingly operate over distributed, re…

cs.DB2025

Determining Window Sizes using Species Estimation for Accurate Process Mining over Streams

Christian Imenkamp, Martin Kabierski, Hendrik Reiter +3

Streaming process mining deals with the real-time analysis of event streams. A common approach for it is to adopt windowing mechanisms that select event data from a stream for subs…

cs.PF2025

Ecoscape: Fault Tolerance Benchmark for Adaptive Remediation Strategies in Real-Time Edge ML

Hendrik Reiter, Ahmad Rzgar Hamid, Florian Schlösser +2

Edge computing offers significant advantages for realtime data processing tasks, such as object recognition, by reducing network latency and bandwidth usage. However, edge environm…

cs.ET2025

Process Mining on Distributed Data Sources

Maximilian Weisenseel, Julia Andersen, Samira Akili +10

Major domains such as logistics, healthcare, and smart cities increasingly rely on sensor technologies and distributed infrastructures to monitor complex processes in real time. Th…

cs.SE2025

DPM-Bench: Benchmark for Distributed Process Mining Algorithms on Cyber-Physical Systems

Hendrik Reiter, Patrick Rathje, Olaf Landsiedel +1

Process Mining is established in research and industry systems to analyze and optimize processes based on event data from information systems. Within this work, we accomodate proce…