TY - GEN
T1 - A Containerized Microservice Architecture for a ROS 2 Autonomous Driving Software
T2 - 30th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2024
AU - Betz, Tobias
AU - Wen, Long
AU - Pan, Fengjunjie
AU - Kaljavesi, Gemb
AU - Zuepke, Alexander
AU - Bastoni, Andrea
AU - Caccamo, Marco
AU - Knoll, Alois
AU - Betz, Johannes
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The automotive industry is transitioning from traditional ECU-based systems to software-defined vehicles. A central role of this revolution is played by containers, lightweight virtualization technologies that enable the flexible consolidation of complex software applications on a common hardware platform. Despite their widespread adoption, the impact of containerization on fundamental real-time metrics such as end-to-end latency, communication jitter, as well as memory and CPU utilization has remained virtually unexplored. This paper presents a microservice architecture for a real-world autonomous driving application where containers isolate each service. Our comprehensive evaluation shows the benefits in terms of end-to-end latency of such a solution even over standard bare-Linux deployments. Specifically, in the case of the presented microservice architecture, the mean end-to-end latency can be improved by 5-8%. Also, the maximum latencies were significantly reduced using container deployment.
AB - The automotive industry is transitioning from traditional ECU-based systems to software-defined vehicles. A central role of this revolution is played by containers, lightweight virtualization technologies that enable the flexible consolidation of complex software applications on a common hardware platform. Despite their widespread adoption, the impact of containerization on fundamental real-time metrics such as end-to-end latency, communication jitter, as well as memory and CPU utilization has remained virtually unexplored. This paper presents a microservice architecture for a real-world autonomous driving application where containers isolate each service. Our comprehensive evaluation shows the benefits in terms of end-to-end latency of such a solution even over standard bare-Linux deployments. Specifically, in the case of the presented microservice architecture, the mean end-to-end latency can be improved by 5-8%. Also, the maximum latencies were significantly reduced using container deployment.
KW - Autonomous Driving
KW - Containerization
KW - End-to-End Latency
KW - Robot Operating System 2
KW - Software-Defined Vehicle
UR - http://www.scopus.com/inward/record.url?scp=85207091251&partnerID=8YFLogxK
U2 - 10.1109/RTCSA62462.2024.00018
DO - 10.1109/RTCSA62462.2024.00018
M3 - Conference contribution
AN - SCOPUS:85207091251
T3 - Proceedings - 2024 IEEE 30th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2024
SP - 57
EP - 66
BT - Proceedings - 2024 IEEE 30th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 August 2024 through 23 August 2024
ER -