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

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Detalles Bibliográficos
Publicado en:arXiv.org (Dec 13, 2024), p. n/a
Autor principal: Long, Wen
Otros Autores: Rickert, Markus, Pan, Fengjunjie, Lin, Jianjie, Zhang, Yu, Betz, Tobias, Knoll, Alois
Publicado:
Cornell University Library, arXiv.org
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Acceso en línea:Citation/Abstract
Full text outside of ProQuest
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022 |a 2331-8422 
035 |a 3145273968 
045 0 |b d20241213 
100 1 |a Long, Wen 
245 1 |a Virtualization & Microservice Architecture for Software-Defined Vehicles: An Evaluation and Exploration 
260 |b Cornell University Library, arXiv.org  |c Dec 13, 2024 
513 |a Working Paper 
520 3 |a 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%. 
653 |a Software 
653 |a Central processing units--CPUs 
653 |a Computer memory 
653 |a Electronic systems 
653 |a Performance evaluation 
653 |a Intelligent vehicles 
653 |a Computer architecture 
653 |a Electronic control 
653 |a Software development 
653 |a Cloud computing 
653 |a Control equipment 
653 |a Vehicles 
700 1 |a Rickert, Markus 
700 1 |a Pan, Fengjunjie 
700 1 |a Lin, Jianjie 
700 1 |a Zhang, Yu 
700 1 |a Betz, Tobias 
700 1 |a Knoll, Alois 
773 0 |t arXiv.org  |g (Dec 13, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3145273968/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2412.09995