| Title | Performance Analysis of Open-Source Hypervisors for Automotive Systems |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Zhang, Zhengjun, Liu, Yanqiang, Chen, Jiangtao, Qi, Zhengwei, Zhang, Yifeng, Liu, Huai |
| Conference Name | 2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS) |
| Keywords | ARM virtualization, automotive, Benchmarking, Hardware, i-o systems security, Instruction sets, Interference, Jitter, Linux, Performance, pubcrawl, Real-time, Real-time Systems, Scalability, Virtual machine monitors |
| Abstract | Nowadays, automotive products are intelligence intensive and thus inevitably handle multiple functionalities under the current high-speed networking environment. The embedded virtualization has high potentials in the automotive industry, thanks to its advantages in function integration, resource utilization, and security. The invention of ARM virtualization extensions has made it possible to run open-source hypervisors, such as Xen and KVM, for embedded applications. Nevertheless, there is little work to investigate the performance of these hypervisors on automotive platforms. This paper presents a detailed analysis of different types of open-source hypervisors that can be applied in the ARM platform. We carry out the virtualization performance experiment from the perspectives of CPU, memory, file I/O, and some OS operation performance on Xen and Jailhouse. A series of microbenchmark programs have been designed, specifically to evaluate the real-time performance of various hypervisors and the relevant overhead. Compared with Xen, Jailhouse has better latency performance, stable latency, and little interference jitter. The performance experiment results help us summarize the advantages and disadvantages of these hypervisors in automotive applications. |
| DOI | 10.1109/ICPADS53394.2021.00072 |
| Citation Key | zhang_performance_2021 |
Performance Analysis of Open-Source Hypervisors for Automotive Systems