Comparative assessment of Time-Sensitive Networking transmission schemes in automotive applications

Time-Sensitive Networking (TSN) has emerged as a promising communication technology for automotive applications. The TSN standards provide a flexible toolkit, enabling network designers to select the features and mechanisms that best suit the application context requirements. TSN facilitates the man...

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Bibliographic Details
Published in2023 AEIT International Conference on Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE) pp. 1 - 6
Main Authors Testa, Giuseppe, Canzonieri, Giuliano, Leonardi, Luca, Bello, Lucia Lo, Patti, Gaetano
Format Conference Proceeding
LanguageEnglish
Published AEIT 17.07.2023
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Summary:Time-Sensitive Networking (TSN) has emerged as a promising communication technology for automotive applications. The TSN standards provide a flexible toolkit, enabling network designers to select the features and mechanisms that best suit the application context requirements. TSN facilitates the management of diverse traffic flows through a single channel by defining transmission schemes and protocols. However, some automotive applications, such as the automated driving ones, require the support for event-driven real-time traffic, but the TSN support for this kind of flows is limited. To overcome this limitation, a recent research proposed an online Earliest Deadline First-based scheduling approach, called Deadline-TSN, able to handle various traffic classes (including the event-driven ones) in a uniform way. Deadline-TSN supports real-time traffic, but is not designed to support deterministic communications. For this reason, this paper investigates the adoption of TSN to build network setups for managing diverse kinds of in-car traffic flows, i.e., periodic and event-driven, with diverse timing constraints and presents a comparative performance evaluation between a configuration exploiting a combination of multiple TSN transmission schemes and Deadline-TSN in a realistic automotive scenario.