With the rise of Industry 4.0, industrial networks require not only low-latency and deterministic communication but also robust and integrated security solutions. Time-Sensitive Networking (TSN) provides a suite of standards that enable precise timing and predictable communication over Ethernet, which is critical for real-time industrial protocols like PROFINET and OPC UA Pub/Sub. However, integrating advanced security features into these protocols while maintaining real-time performance presents a significant challenge.

This thesis aims to investigate and optimize secure communication for these industrial protocols over TSN-enabled Linux systems. The evaluation will be conducted using the open-source Real-Time Communication (RTC) testbench, allowing reproducible measurements of key performance metrics under different system and hardware configurations.

Objectives:

• Implement secure communication features (e.g., encryption and authentication) for PROFINET and OPC UA Pub/Sub protocols with TSN support on a Linux platform.
• Evaluate the performance metrics such as jitter, cycle times, throughput, and latency, alongside security measures, using an RTC testbench.
• Test and optimize these metrics across different hardware configurations, including NICs and CPUs.
• Identify best practices and configurations for achieving optimal network performance and security. 

Testing and Evaluation:

• Utilize the RTC testbench to simulate network conditions and measure performance metrics, including security overhead.
• Conduct experiments with and without encryption to assess the impact on jitter, latency, cycle times, and throughput.
• Perform tests across different hardware setups, varying NICs, TPM and CPUs to evaluate their impact on network performance and security.
• Analyze data collected from the RTC testbench to validate the effectiveness of the implemented solutions.

5G networks increasingly serve mission-critical applications such as industrial automation, autonomous vehicles, and remote control. These use cases require highly deterministic communication with strict bounds on latency, jitter, and reliability. Time-Sensitive Networking (TSN), originally designed for wired industrial Ethernet, provides mechanisms for deterministic communication and is now being integrated with 5G to provide mobility. 

Although several reliability mechanisms exist, such as Frame Replication and Elimination for Reliability (FRER) and adaptive Modulation and Coding Scheme (MCS), their usage is typically fixed or manually configured. Real 5G environments, however, exhibit dynamic and sometimes unpredictable wireless channel conditions. This leads to the need for a Central Network Controller that dynamically applies the best reliability mechanism.

This thesis aims to simulate and analyze the dynamic management of reliability measures (e.g., FRER, MCS adaptation, and resource allocation) in TSN-5G networks, and evaluate their performance under varying channel conditions.

Autonomous drone swarms are rapidly evolving from a purely academic research topic into a key industrial technology. Application areas range from cooperative surveying and environmental monitoring to search-and-rescue missions, as well as coordinated logistics or inspection tasks in complex environments. All of these applications require a highly precise shared time base with deviations clearly below one millisecond.

At the same time, drone swarms face particular challenges: fluctuating radio channels due to rapid movement, heterogeneous hardware clocks, limited onboard computing resources, GPS shadowing, or targeted jamming/spoofing attacks. The project work to be created contributes to systematically evaluating existing methods for their suitability in this demanding domain and to outlining a prototypical solution.

The goal of this project is to identify suitable mechanisms for time synchronisation in heterogeneous drone swarms, to evaluate them comparatively, and to implement at least one method in a prototype and verify it experimentally.

To this end, an application-oriented requirements profile should first be created and the state of the art analysed. The most promising approach is then to be implemented in a simulation or on a real or emulated UAV testbed. Finally, the measurement results, regarding synchronisation accuracy, robustness, overhead, and scalability, are to be documented, and recommendations for future swarm systems derived.

Deterministic, low-latency communication for time-sensitive data is a critical challenge in industrial and automotive networks. IEEE introduced the Ethernet standards Time-Sensitive Networking (TSN) to address these requirements. Using traffic prioritization and scheduling, TSN enables deterministic, reliable, and low-latency communication. However, industry 4.0 has intensified the need for mobility, such as using Automated Guided Vehicles (AGVs). To meet these demands, 5G must be integrated into TSN systems.
To explore the integration of 5G and TSN, a TSN-5G testbed is build to evaluate end-to-end schedulers and reliability concepts.

The Wireless Sensor Networks lab offers the opportunity to develop software solutions for the wireless sensor networking system, targeting innovative applications. For the next semester, a position is available to assist the participants in learning the programming environment and during the project development phase. The lab is planned to be held on-site every Tuesday 15:00 to 17:00.

Voraussetzungen