Performance Analysis of KVM Hypervisor Using a Self-Driving Developer Kit

Thilo Muller, Hadi Askaripoor, Alois Knoll

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

2 Zitate (Scopus)

Abstract

Virtualization plays an increasingly important role in safety-critical embedded systems like modern vehicles due to its numerous advantages like cost reduction, better scalability, or easier safety verification. These advantages come at the cost of additional performance overhead. While performance evaluation of virtualization solutions for server applications has been the subject of research for a long time, it is still not adequately investigated for embedded use cases. We present the first work to analyze the performance of KVM, an open-source hypervisor, on an Nvidia Drive AGX, a developer kit for self-driving vehicles. Experimental measurements show that the computational overhead restricts the number of partitions. Also, poor memory and file I/O performance suggest that KVM is not usable for practical applications with the Nvidia Drive AGX.

OriginalspracheEnglisch
TitelIECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
Herausgeber (Verlag)IEEE Computer Society
ISBN (elektronisch)9781665480253
DOIs
PublikationsstatusVeröffentlicht - 2022
Veranstaltung48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 - Brussels, Belgien
Dauer: 17 Okt. 202220 Okt. 2022

Publikationsreihe

NameIECON Proceedings (Industrial Electronics Conference)
Band2022-October
ISSN (Print)2162-4704
ISSN (elektronisch)2577-1647

Konferenz

Konferenz48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022
Land/GebietBelgien
OrtBrussels
Zeitraum17/10/2220/10/22

Fingerprint

Untersuchen Sie die Forschungsthemen von „Performance Analysis of KVM Hypervisor Using a Self-Driving Developer Kit“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren