Real-time TSN communication

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

• Quantifying the Impact of Frame Preemption on Combined TSN Shapers
  Rubi Debnath, Philipp Hortig, Luxi Zhao, Sebastian Steinhorst
  IEEE/IFIP Network Operations and Management Symposium (NOMS 2024), Seoul, South Korea, 2024, pp. 1-9.
• 5GTQ: QoS-Aware 5G-TSN Simulation Framework
  Rubi Debnath, Mustafa Selman Akinci, Devika Ajith, and Sebastian Steinhorst
  2023 IEEE 98th Vehicular Technology Conference: VTC2023-Fall, Hong Kong, 2023, pp. 1-7.
• Advanced Modeling and Analysis of Individual and Combined TSN Shapers in OMNeT++
  Rubi Debnath, Philipp Hortig, Luxi Zhao, Sebastian Steinhorst
  2023 IEEE 29th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), Niigata, Japan, 2023, pp. 1-10.