Real-time TSN communication

Duration: 3 years, 01.03.2021 – 30.05.2024

Partners:

  • Professur für Embedded Systems and Internet of Things (TUM-ESI), Prof. Dr. Sebastian Steinhorst 
  • Guest Scientist (Beihang University, China), Prof. Dr. Luxi Zhao
Project Lead:

Prof. Dr. Sebastian Steinhorst (sebastian.steinhorst@tum.de)

Contact:

Rubi Debnath, MSc (rubi.debnath@tum.de)

Project Objectives

Time-Sensitive Networking (TSN) is a layer-2 technology standardized by IEEE 802.1. Time-Sensitive and Deterministic Networking is receiving significant interest from academia and industry. TSN aims to provide the necessary mechanisms for delivering time-critical and latency-sensitive data in industrial automation, automotive, and other industries where precise timing and low latency are crucial. TSN incorporates various IEEE standards, such as IEEE 802.1Qbv (time-aware shaper), 802.1Qbu/802.3br (frame preemption), 802.1Qca (per-stream filtering and policing), 802.1Qcc (stream reservation protocol), etc. These standards work together to ensure time synchronization, traffic scheduling, and network management capabilities.

The objective of this project is to develop an intelligent configuration framework for Time-Sensitive Networking (TSN) that enables dynamic adaptation and optimization of TSN network parameters and configurations in real-time. The goal is to enhance the flexibility, scalability, and performance of TSN systems by allowing them to adapt to changing network conditions, application requirements, and resource constraints during runtime. The project aims to design and implement algorithms for the configuration of large-scale industrial networks. The developed framework will be validated through experiments with extensive simulations to demonstrate its effectiveness in achieving dynamic adaptability and optimization in large-scale industrial networks.

 

Contact Information

If you are interested in this topic, and you are looking for a bachelor's thesis, master's thesis, or research internship, feel free to contact: 

  1. M. Sc. Rubi Debnath

Related Publications

2023

  • Rubi Debnath, Philipp Hortig, Luxi Zhao, Sebastian Steinhorst. "Advanced Modeling and Analysis of Individual and Combined TSN Shapers in OMNeT++". In Press: The 29th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’23). Niigata, Japan.