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Cyber-physical systems across application domains are getting increasingly complex, driven by five technological and market trends: 1) all current design parameters, e.g. number of interfaces, are increasing by an order of magnitude, 2) increased customization of systems at design time, 3) continuous evolution of systems after deployment, 4) increased system autonomy, and 5) integration into distributed systems-of-systems. The consequences of increasing complexity are visible in daily practice in which Dutch industry struggles to efficiently develop correct and well-performing cyber-physical systems.
In line with TNOs goal to increase competitiveness of Dutch industry, my research aims to address increasing complexity through new model-based design methodologies. These are methodologies in which abstraction, provided by models used for specification, communication, analysis, simulation, or synthesis, play an essential role in reducing development time and overall system cost. A key part of this research is to investigate how models can be used to automatically generate parts of complex systems that are guaranteed to provide the specified functionality at exactly the right time. For example, to ensure that an airbag immediately inflates correctly in the event of a car crash, which requires both correct and timely interactions between hardware and software.
A recent highlight is the publication and warm reception of the first ever empirical survey-based study into industry practice in real-time systems. There is a great need for this line of research in the area of real-time systems to ensure that academic research can be conducted with a better understanding of the current state of the practice and future trends. I hope this first work inspires the real-time community to make empirical research a well-established part of the field going forward.Much of my recent technical research advances the state-of-the-art in mixed-criticality real-time systems. This type of systems are found e.g. in the avionics and rail domains and are characterized by applications with different safety requirements sharing hardware resources, such as processors, memories, and caches. The results involve mapping and scheduling techniques, along with resource budgeting methods that reduce development time, and schedulability analyses that allows timing requirements to be analytically verified. These techniques promote efficient resource usage by considering variations in supply and demand of resources during execution, e.g. in response to a mode-switch, which may reduce the cost of the platform. It also promotes safety by temporally isolating applications, which may reduce the time and cost of safety certification.