Demo: Interactive Off-the-Shelf In-Car TSN Testbed
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
Abstract
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.
Details
Original language | English |
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Title of host publication | 15th IEEE Vehicular Networking Conference (VNC 2024) |
Editors | Susumu Ishihara, Hiroshi Shigeno, Onur Altintas, Takeo Fujii, Raphael Frank, Florian Klingler, Tobias Hardes, Tobias Hardes |
Place of Publication | Kobe, Japan |
Publisher | IEEE |
Pages | 267-268 |
Number of pages | 2 |
ISBN (electronic) | 9798350362701 |
Publication status | Published - May 2024 |
Peer-reviewed | Yes |
External IDs
Scopus | 85198388341 |
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Mendeley | f7cbddf0-1b1d-3997-a7c9-3a56ca45af49 |