Kolloquiumsvortrag: 27. November 2018, Anna Arestova


November 27, 2018
10:15to11:00

Konzept und Umsetzung eines Centralized Network Controllers für Time-Sensitive Networks

With Time-Sensitive Networking (TSN), the IEEE 802.1Q workgroup is expanding the Ethernet standard to determinism and real-time capability for a commo  basis for real-time communication systems via Ethernet. The heterogeneity and incompatibility of existing procedures makes development and extension of real-time communication methods in a common network difficult. Using the time synchronization substandards from IEEE 802.1AS, the time-aware shaper from IEEE 802.1Qbv and the TSN configuration models from IEEE 802.1Qcc, TSN allows to give timing guarantees and bandwidth reservation for critical time-triggered traffic and also bandwidth guarantees for further traffic classes based on a TDMA principle. A central unit, the Centralized Unit Network Controller (CNC), is in charge of the actual TSN configuration in a hybrid and fully centralized TSN configuration model. Since the idea of a CNC has been introduced in the 802.1Qcc standard but not concretized yet, big companies are thinking about a possible concept of a CNC, without disclosing concrete results and implementations. That is why a concept for the CNC in a fully centralized TSN configuration model from IEEE 802.1Qcc with the focus on the scheduling is examined and worked out in this thesis. Related publications will be analyzed to the scheduling mechanism and extended. Additionally, important parameters for the tasks of the CNC and in particular for the scheduling will be identified. In the analysis part, it will be shown how latencies are satisfied and jitter is minimized by the TSN substandards and by the scheduling. Nevertheless, it will be explained which restriction has to be made due to the performance of the scheduling mechanism. Finally, it will be discussed how a TSN configuration can be made more efficient regarding bandwidth utilization.

Ort: Raum 04.137, Martensstr. 3, Erlangen