Anna Kosmalska

Reconciling safety, performance and reliability in cloud-based cognitive systems is no easy task. Especially in safety-critical autonomous systems such as driverless cars, expectations rightly assume that all three requirements are implemented at the highest level. However, this comes up against limited resources. The Fraunhofer IKS has developed an approach for optimising safety, performance and reliability depending on the current situation and concrete applications: flexilience.

Addressing the wide range of challenges in dependable cloud-based cyber-physical systems of systems (CPSoS) requires new approaches that are automated and efficient enough to shift some of the system’s elements to runtime. To design and evaluate the system architecture, Fraunhofer IKS has developed an iterative and automated process.

The future will rely on widespread, massively-connected, highly-intelligent systems. To implement this vision, we need dependable cloud-based cyber-physical systems. Research in this direction encounters as many opportunities as challenges. Such systems exist in changing environments and interact with other systems and humans, which requires intelligence, autonomy, safety and adaptability – in fact, conflicting goals. An example of this is autonomous driving.