Bare-Metal vs. Hypervisors and Containers: Performance Evaluation of Virtualization Technologies for Software-Defined Vehicles

Software-defined vehicles (SDV) play an important role in future electrical and electronic (E&E) architectures. Their increased flexibility compared to traditional architectures is a crucial factor in the rapid development cycles of autonomous driving. Containerization and virtualization are two key technologies that enable rapid software installation and updates under the SDV framework. These two technologies have been widely adopted in cloud computing, but their performance and suitability in intelligent vehicles still has to be evaluated. In this work, we look at generic performance experiments of containerization and virtualization on both embedded and general-purpose computer systems regarding CPU, memory, network, and disk. We further investigate the impact of virtualization and containerization on the Autoware framework to evaluate scenarios that are close to real-world automotive applications. Additionally, we evaluate performance by splitting the Autoware framework into several dependent service parts, which are installed in separate containers. Extensive experimental results show that virtualization and containerization have no significant performance drop with 0-5% loss compared to a bare-metal setup in terms of CPU, memory, and network. However, both technologies suffer dramatic performance degradation on the disk side, losing 5-15% in containers and 35% in virtualization.