对比容器与虚拟化在车载系统中的性能，发现对实际自动驾驶应用影响极小。
Virtualization & Microservice Architecture for Software-Defined Vehicles: An Evaluation and Exploration
- 在嵌入式与高性能平台测试容器和虚拟化技术的资源开销。
- 相比裸机部署，性能下降0-5%（计算/内存/网络），磁盘操作下降最多35%。
- 微服务架构可提升启动速度18%，适合智能汽车软件迭代需求。
软件定义汽车（SDV）正推动车载电子电气架构从分散的电子控制单元（ECUs）向集中式计算平台演进，以应对日益复杂的系统需求和功能扩展。容器化与虚拟化技术虽在云计算中广泛应用，但在智能汽车场景下的性能与适用性仍缺乏充分评估。本文在AMD64与ARM64嵌入式及高性能系统上，全面评估了容器化与虚拟化在CPU、内存、网络和磁盘方面的表现。实验结果显示，相较于裸机环境，两者在计算、内存和网络使用上仅出现0-5%的轻微性能下降，而磁盘操作则显著降低：容器化环境下降5-15%，虚拟化环境最高达35%。进一步基于Autoware框架测试真实车载应用，结果表明性能影响可忽略；此外，集成微服务架构后，系统启动时间最多优化18%，展现出良好的可维护性与响应能力。
原文摘要 · Abstract (English)
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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