Virtualization & Microservice Architecture for Software-Defined Vehicles: An Evaluation and Exploration
Long Wen, Markus Rickert, Fengjunjie Pan, Jianjie Lin, Yu Zhang,, Tobias Betz, and Alois Knoll

TL;DR
This paper evaluates virtualization and microservice architectures in Software-Defined Vehicles, showing minimal performance impact and potential startup time improvements, thus supporting their adoption in automotive systems.
Contribution
It provides a comprehensive performance analysis of containerization and virtualization in SDVs, including their effects on real automotive applications and microservice architecture integration.
Findings
Performance decline of 0-5% in CPU, memory, network
Disk operations reduced by 5-15% in containerized environments
Microservice architecture can improve startup time by up to 18%
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…
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