Bridging the Pragmatic Gaps for Mixed-Criticality Systems in the Automotive Industry

An increasingly important trend in the design of safety-critical systems is the integration of components with different levels of criticality onto a common hardware platform. Mixed-criticality systems (MCSs) have been well researched in academia, but can be difficult to implement in industrial scenarios as the theoretical models underpinning the research do not sufficiently consider industrial safety practice and safety standards. In this article, we make the first attempt toward the implementation of the MCS theoretical model in industrial settings. To this end, we identify the pragmatic gaps between theory and practice, and then propose a generic industrial MCS architecture, termed P-MCS (Practical-MCS). P-MCS is built upon the conventional theoretical MCS model with additional considerations of industrial safety requirements: 1) runtime safety analysis, determining preserved applications in each system mode and 2) correct partitioning and isolation of different critical elements. We introduce three implementing methods for P-MCS. Corresponding to the new system architecture, we present a theoretical model and schedulability analysis (with consideration of shared resources) to ensure system predictability. Finally, we evaluate and demonstrate P-MCS in terms of system schedulability, overheads, throughput, and predictability, along with a real-world case study. As shown in the evaluation, the considerations of industrial requirements lead to extra overheads and performance reduction in P-MCS. Such weaknesses can be considerably mitigated by hardware assistance and acceleration.