Automating End Station Configuration: An Agile Approach to Time-Sensitive Networking

Sammanfattning: Industries such as automotive and industrial automation are pushing the limits of networking technology. The Time-Sensitive Networking (TSN) standards offer a promising solution that can meet the demands of high-bandwidth applications with strict timing constraints, allowing time-critical traffic to coexist with other traffic. However, TSN is relatively new, with much research necessary before it is usable in the industry. This thesis addresses the problem of the common manual configuration of end stations, being time-consuming and error-prone. Through exploring the TSN standards, this thesis attempts to solve the configuration problem by providing a proof-of-concept for both design and implementation of a software architecture managing the end stations and automating their configuration process. Adopting an agile and iterative approach made the complexity of TSN manageable. Furthermore, this thesis has been guided by the research question: How can the configuration of a TSN end station be automated? The design was split into three components: an interface, a configuration manager, and a TSN library. In addition, a communication protocol between the end stations and the Centralized Network Configuration (CNC) is established. The implementation of the proposed design used Python for all three modules in the end station management software, with the REST protocol for the interface. After presenting the implementation, it was evaluated to show the performance of the implemented end station management software. The results showed that the management software would likely not be the bottleneck, as other components it depends on are considerably slower. This thesis and its research contribution offer a practical foundation for continued research and development, such as investigating the configuration of the end stations, providing proofs-of-concept for engineering tools with specific use cases, and finalizing a TSN system.