Usage of AI methods for the parametrization of convergent, deterministic, industrial networks (KIKDIN)
Partner | Siemens Predevelopment Nürnberg |
Funded period | July 2019 - September 2020 |
Researcher | Dr. Michael Seufert |
Project Description
Within the “KIKDIN” project, the chair of communication networks of the University of Würzburg and SIEMENS investigate the usage of AI methods for the parametrization of convergent, deterministic, industrial networks. The long-term goal is to assign and parametrize network configurations for different application types and different network infrastructures in an automated and dynamic way. The assignment shall be based on statistical methods, which especially includes the usage of machine learning as an AI method.
Figure 1: Time-Sensitive Networking Components [Source: Farkas J., Introduction to IEEE 802.1 (focus on TSN TG)]