TSN shapers enable local latency control for Ethernet networks
Decentralized Latency Models and Information Flow for TSN Shapers - A Tutorial
Networking and Internet Architecture
Summary
Industrial and in-vehicle networks now use Ethernet with special timing controls to keep delays predictable and avoid loss. The authors show how different ways of controlling traffic—called shapers—can be analyzed locally on each network switch without knowing the whole network. They provide clear ways to calculate delay for various shapers and test five models to see how well they handle latency, jitter, and traffic load. Their findings help understand which shaping methods work best depending on network setup and traffic types.
What this means in practice
- •For industrial network engineers: Calculate tight latency bounds on switches in automated factory networks using local information to ensure timing guarantees.
- •For automotive communication designers: Choose and configure Ethernet traffic shapers that best fit real-time vehicle network constraints based on measured latency and jitter performance.
Authors
Alexej Grigorjew, Stefan Geissler, Jürgen Schmitt, Tobias Hossfeld
Abstract
Recent advancements in the fields of industrial automation and in-vehicle communication have also increased the requirements on their underlying networks. Traditional field bus technologies are being replaced by regular Ethernet devices with features from the IEEE Time-Sensitive Networking working group. Their standards are designed to achieve zero congestion loss and deterministic latency bounds, but the specific guarantees can differ depending on the shapers used and how the bounds are calculated. After several contributions to the standardization efforts, this work presents a number of decentralized latency models that can be applied locally on the switches, without requiring global knowledge from the rest of the network. It includes a formal definition of delay segments that allows to incorporate interoperability between different shapers and latency models in the future. It presents pseudo-code suggestions for the latency bounds computation of Strict Priority, Credit-Based Shaping, Asynchronous Traffic Shaping, and Cyclic Queuing and Forwarding, all of which can be applied locally on the devices. Finally, five models were implemented and evaluated with respect to their efficiency in terms of latency, jitter, and number of accepted streams. The results illustrate how different shapers are suited for different networks and traffic distributions.