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Real-Time Performance Analysis and Tuning of Embedded System Virtualization Architecture Based on KVM

Real-Time Performance Analysis and Tuning of Embedded System Virtualization Architecture Based on KVM

Deepa Mathew, Bijoy Antony Jose
Copyright: © 2022 |Volume: 13 |Issue: 1 |Pages: 20
ISSN: 1947-3176|EISSN: 1947-3184|EISBN13: 9781683181774|DOI: 10.4018/IJERTCS.302113
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MLA

Mathew, Deepa, and Bijoy Antony Jose. "Real-Time Performance Analysis and Tuning of Embedded System Virtualization Architecture Based on KVM." IJERTCS vol.13, no.1 2022: pp.1-20. http://doi.org/10.4018/IJERTCS.302113

APA

Mathew, D. & Jose, B. A. (2022). Real-Time Performance Analysis and Tuning of Embedded System Virtualization Architecture Based on KVM. International Journal of Embedded and Real-Time Communication Systems (IJERTCS), 13(1), 1-20. http://doi.org/10.4018/IJERTCS.302113

Chicago

Mathew, Deepa, and Bijoy Antony Jose. "Real-Time Performance Analysis and Tuning of Embedded System Virtualization Architecture Based on KVM," International Journal of Embedded and Real-Time Communication Systems (IJERTCS) 13, no.1: 1-20. http://doi.org/10.4018/IJERTCS.302113

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Abstract

Embedded systems are proceeding towards exploiting virtualization technology to have the benefits of Real-Time Operating System (RTOS) and General-Purpose Operating System (GPOS) in the same system. This combination provides both a timely and deterministic behavior and a general-purpose application codebase. There still exist concerns about the real-time responsiveness of RTOS running inside a Virtual Machine (VM). In this paper, the real-time performance of Kernel-based Virtual Machine (KVM) virtualization architecture is analyzed on a multi-core system. Here, a preemptible Linux kernel with the PREEMPT_RT patch is used for RTOS, while a standard Linux kernel is used for GPOS. The interrupt latency inside the real-time guest VM is analyzed by applying various amounts of CPU, memory, and I/O stresses on the guest and host systems. A VM resource monitoring tool ‘VM_stat’ is developed to know the resource usage of the guest VMs, which is useful for effectively tuning the system. Different real-time tuning measures are applied on the host/guest systems and the performance is analyzed.

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