Distributed event factory: a tool for generating event streams on distributed data sources
Distributed event factory: a tool for generating event streams on distributed data sources
In real-life applications, data sources are often distributed. In a smart factory, data is generated by spatially distributed sensors. Distributed process mining algorithms may exploit this data locality by processing data where it is generated. The Distributed Event Factory is a tool to evaluate distributed process mining algorithms under (best-effort) realistic conditions. It generates synthetic event streams that consider the distributed nature of the data sources. In particular, we can evaluate the scalability of such algorithms by increasing the volume and velocity of the generated events. Additionally, other external factors such the temporal behavior of events, and varying load profiles can be configured. Using the example of a smart factory, we demonstrate the tool’s capabilities.
Distributed Computing, Distributed Process Mining, Event Log Generator, Markov Chain, Stream Process Mining
Reiter, Hendrik
a357c35a-95af-4822-ada8-a1f0ba4a7f76
Imenkamp, Christian
5c9bc4b9-d833-4c04-8806-6f511e4e19f7
Koschmider, Agnes
6f04798e-353d-41fe-a4cc-40c7703c65cf
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
15 October 2024
Reiter, Hendrik
a357c35a-95af-4822-ada8-a1f0ba4a7f76
Imenkamp, Christian
5c9bc4b9-d833-4c04-8806-6f511e4e19f7
Koschmider, Agnes
6f04798e-353d-41fe-a4cc-40c7703c65cf
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Reiter, Hendrik, Imenkamp, Christian, Koschmider, Agnes and Hasselbring, Wilhelm
(2024)
Distributed event factory: a tool for generating event streams on distributed data sources.
Doctoral Consortium and Demo Track 2024 at the International Conference on Process Mining, ICPM-D 2024, , Copenhagen, Denmark.
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Conference or Workshop Item
(Paper)
Abstract
In real-life applications, data sources are often distributed. In a smart factory, data is generated by spatially distributed sensors. Distributed process mining algorithms may exploit this data locality by processing data where it is generated. The Distributed Event Factory is a tool to evaluate distributed process mining algorithms under (best-effort) realistic conditions. It generates synthetic event streams that consider the distributed nature of the data sources. In particular, we can evaluate the scalability of such algorithms by increasing the volume and velocity of the generated events. Additionally, other external factors such the temporal behavior of events, and varying load profiles can be configured. Using the example of a smart factory, we demonstrate the tool’s capabilities.
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Published date: 15 October 2024
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© 2024 Copyright for this paper by its authors.
Venue - Dates:
Doctoral Consortium and Demo Track 2024 at the International Conference on Process Mining, ICPM-D 2024, , Copenhagen, Denmark, 2024-10-15
Keywords:
Distributed Computing, Distributed Process Mining, Event Log Generator, Markov Chain, Stream Process Mining
Identifiers
Local EPrints ID: 503402
URI: http://eprints.soton.ac.uk/id/eprint/503402
PURE UUID: ee2dc75c-028e-447e-9679-956036ffc069
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Date deposited: 30 Jul 2025 16:52
Last modified: 31 Jul 2025 02:09
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Contributors
Author:
Hendrik Reiter
Author:
Christian Imenkamp
Author:
Agnes Koschmider
Author:
Wilhelm Hasselbring
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