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arXiv · 2412.09995

Virtualization & Microservice Architecture for Software-Defined Vehicles: An Evaluation and Exploration

Long Wen·Markus Rickert·Fengjunjie Pan·Jianjie Lin·Yu Zhang·Tobias Betz·Alois Knoll
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Abstract

The emergence of Software-Defined Vehicles (SDVs) signifies a shift from a distributed network of electronic control units (ECUs) to a centralized computing architecture within the vehicle's electrical and electronic systems. This transition addresses the growing complexity and demand for enhanced functionality in traditional E/E architectures, with containerization and virtualization streamlining software development and updates within the SDV framework. While widely used in cloud computing, their performance and suitability for intelligent vehicles have yet to be thoroughly evaluated. In this work, we conduct a comprehensive performance evaluation of containerization and virtualization on embedded and high-performance AMD64 and ARM64 systems, focusing on CPU, memory, network, and disk metrics. In addition, we assess their impact on real-world automotive applications using the Autoware framework and further integrate a microservice-based architecture to evaluate its start-up time and resource consumption. Our extensive experiments reveal a slight 0-5% performance decline in CPU, memory, and network usage for both containerization and virtualization compared to bare-metal setups, with more significant reductions in disk operations-5-15% for containerized environments and up to 35% for virtualized setups. Despite these declines, experiments with actual vehicle applications demonstrate minimal impact on the Autoware framework, and in some cases, a microservice architecture integration improves start-up time by up to 18%.

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Long Wen, Markus Rickert, Fengjunjie Pan, Jianjie Lin, Yu Zhang, Tobias Betz, Alois Knoll. 2024-12-13. Virtualization & Microservice Architecture for Software-Defined Vehicles: An Evaluation and Exploration. https://arxiv.org/abs/2412.09995

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