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Project

KITOS

Künstliche Intelligenz zur dynamischen Optimierung des Netzwerkmanagements

Künstliche Intelligenz zur dynamischen Optimierung des Netzwerkmanagements

  • Duration:

The overall goal is to provide industrial networks with the necessary dynamics and methods for self-healing and self-optimization in order to generate the necessary agility and reliability that future production processes in Industry 4.0 require. TSN is used as the basis for networking. Kl algorithms are developed which support configuration tools in decision making in order to achieve a more efficient use of resources as well as higher performance configurations. For active operation, the network management is hardened against failures by means of Kl supported error detection and adaptation mechanisms.

Partners

Assoziierte Partner:

Sponsors

BMBF - Federal Ministry of Education and Research

16KIS1158K

BMBF - Federal Ministry of Education and Research

Publications about the project

Maximilian Berndt; Christoph Fischer; Dennis Krummacker

In: 2020 1st Workshop on Next Generation Networks and Applications (NGNA). Workshop on Next Generation Networks and Applications (NGNA-2020), December 14-18, Kaiserslautern, Germany, Technische Universität Kaiserslautern, Kaiserslautern, 12/2020.

To the publication

Christoph Fischer; Maximilian Berndt; Dennis Krummacker

In: 2020 1st Workshop on Next Generation Networks and Applications (NGNA). Workshop on Next Generation Networks and Applications (NGNA-2020), December 14-18, Kaiserslautern, Germany, Technische Universität Kaiserslautern, Kaiserslautern, 12/2020.

To the publication

Christoph Fischer; Maximilian Berndt; Dennis Krummacker; Janis Zemitis; Daniel Fraunholz; Hans Dieter Schotten

In: YEF ECE. IEEE Young Engineers Forum (ECE-2020), IEEE, 2020.

To the publication