Pareto-efficient deployment synthesis for safety-critical applications in seamless model-based development

abstract

Increasingly complex functionality in automotive applications demand more and more computing power. As room for computing units in modern vehicles dwindles, centralized ar-chitectures-with larger, more powerful processing units-are the trend. With this trend, applications no longer run on dedicated hardware, but share the same computing resources with others on the centralized platform. Ascertaining efficient deployment and scheduling for co-located applications is complicated by the extra constrains which arise if some of them have a safety-critical functionality. Building on our pre-existing design space exploration solution, we integrated safety constraints, such as ASIL and HW failure rates, as well as practical aspects, such as component costs, and extended the approach to allow for multi-criteria optimization. The work was implemented into our seamless model-based research CASE tool AutoFOCUS3 and evaluated using a non-trivial industrial-inspired case study. The solution is capable of synthesizing deployments together with corresponding schedules, which satisfy different safety and resource constraints. The deployments can subsequently be integrated into the safety case argumentation of AutoFOCUS3, leveraging the tool's seamless capabilities to support safety evidence and certification. Moreover, we are not interested in merely valid solutions, but in good ones. We hence developed a multi-objective optimization algorithm, which synthesizes solutions pareto-optimized for safety, resource usage, timing and any other constraints the user defines. Our approach demonstrates the feasibility and effectiveness of using formal methods to generate correct solutions for safety-critical applications, increasing the confidence and validity of safety cases.