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Reducio - Data Aggregation and Stability Detection for Industrial Processes Using In-Network Computing

Authors: Tirpitz, Liam; Kunze, Ike;

Reducio - Data Aggregation and Stability Detection for Industrial Processes Using In-Network Computing

Abstract

In the following you can find the sourcecode of Reducio, presented in our DEBS'25 paper "Reducio: Data Aggregation and Stability Detection for Industrial Processes Using In-Network Computing" If you use any portion of our work, please consider citing our publication. @Inproceedings { 2025-tirpitz-reducio, author = {Tirpitz, Liam and Kunze, Ike and Niemietz, Philipp and Gerhardus, Kathrin and Bergs, Thomas and Wehrle, Klaus and Geisler, Sandra}, title = {Reducio: Data Aggregation and Stability Detection for Industrial Processes Using In-Network Computing}, booktitle = {Proceedings of the 19th ACM International Conference on Distributed and Event-based Systems (DEBS '25)}, year = {2025}, month = {6}, publisher = {ACM}, doi = {10.1145/3701717.3730547} }

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average