Today, we are witnessing the increasing use of the cloud and virtualization technologies, which are a prominent way for the industry to develop mixed-criticality systems (MCSs) and reduce SWaP-C factors (size, weight, power, and cost) by flexibly consolidating multiple critical and non-critical software on the same System-on-a-Chip (SoC). Unfortunately, using virtualization leads to several issues in assessing isolation aspects, especially temporal behaviors, which must be evaluated due to safety-related standards (e.g., EN50128 in the railway domain). This study proposes a systematic approach for verifying temporal isolation properties in virtualized MCSs to characterize and mitigate timing failures, which is a fundamental aspect of dependability. In particular, as proof of the effectiveness of our proposal, we exploited the real-time flavor of Xen hypervisor used to deploy a virtualized 2 out of 2-based MCS scenario provided in the framework of an academic-industrial partnership, in the context of the railway domain. The results point out that virtualization overhead must be carefully tuned in a real industrial scenario according to the several features provided by a specific hypervisor solution. Further, we identify a set of directions toward employing virtualization in industry in the context of ARM-based mixed-criticality systems.
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Cinque et al. (2024) studied this question.
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