Modern automotive networks based on Time-Sensitive Networking (TSN) are becoming increasingly complex. While hands-on experience is critical to understanding these concepts, the complexity and cost associated with TSN technologies often make practical training inaccessible. As an alternative, network simulation tools have been widely adopted, but they lack interactivity and immediate feedback. To bridge this gap, we propose an interactive and affordable TSN testbed built using off-the-shelf hardware. Our solution provides a user-friendly interface for configuring the testbed and experiencing real-time interactions, such as assessing the impact of background noise traffic on automotive LiDAR sensor data. We demonstrate the functionality of our testbed and provide open-source access to the source code, aiming to improve the quality of TSN training and live experimentation.


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    Titel :

    Demo: Interactive Off-the-Shelf In-Car TSN Testbed


    Beteiligte:


    Erscheinungsdatum :

    29.05.2024


    Format / Umfang :

    2562131 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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