Deutsch Intern
Chair of Computer Science III

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
Alexej Grigorjew M. Sc.
Nikolas Wehner M. Sc.

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.

Time-Sensitive Networking Components [Source: Farkas J., Introduction to IEEE 802.1 (focus on TSN TG)]

Figure 1: Time-Sensitive Networking Components [Source: Farkas J., Introduction to IEEE 802.1 (focus on TSN TG)]