End-to-end Timing Model Extraction from TSN-Aware Distributed Vehicle Software
Bahar Houtan, Mehmet Onur Aybek, Mohammad Ashjaei, Masoud Daneshtalab, Mikael Sjödin, Saad Mubeen · 2022
Extraction of end-to-end timing information from software architectures of vehicular systems to support their timing analysis is a daunting challenge. To address this challenge, this paper presents a systematic method to extract this information from vehicular software architectures that can be distributed over several electronic control units connected by Time-Sensitive Networking (TSN) networks. As a proof of concept, the proposed extraction method is applied to an industrial component model, namely the Rubus Component Model (RCM), and its toolchain. Furthermore, the usability of the proposed method is demonstrated in an industrial use case from the vehicular domain.