@inproceedings{ElsnerMuellerTh{\"u}mmel2019,
  author    = {Elsner, Jesko and Mueller, Rainer and Th{\"u}mmel, S.},
  title     = {Flooded Edge Gateways},
  booktitle = {Automation 2019, 20. Leitkongress der Mess- und Automatisierungstechnik, Autonomous Systems and 5G in Connected Industries, Baden-Baden, DE, 2.-3. Juli, 2019, (VDI-Berichte ; 2351)},
  isbn      = {978-3-18-092351-2},
  pages     = {719 -- 730},
  year      = {2019},
  abstract  = {Increasing numbers of internet-compatible devices, in particular in the context of IoT, usually cause increasing amounts of data. The processing and analysis of a continuously growing amount of data in real-time by means of cloud platforms cannot be guaranteed anymore. Approaches of Edge Computing decentralize parts of the data analysis logics towards the data sources in order to control the data transfer rate to the cloud through pre-processing with predefined quality-of-service parameters. In this paper, we present a solution for preventing overloaded gateways by optimizing the transfer of IoT data through a combination of Complex Event Processing and Machine Learning. The presented solution is completely based on open-source technologies and can therefore also be used in smaller companies.},
  language  = {en}
}