Analyzing goal variability in cyber-physical system networks

Networks of collaborative cyber-physical systems can achieve goals individual systems are incapable of achieving on their own. However, which goals such a network can achieve depends, in part, on the networks current configuration, i.e. its composition of partaking individual systems. As networks of collaborative cyber-physical systems are of a dynamic nature, the composition of such a network can change during runtime, leading to a plethora of often similar, albeit slightly different configurations. Due to the huge number of possible configurations and their various dependencies to the different goals of the network, it is infeasible to handle this amount of information manually. Hence, to provide support for reasoning about dependencies between different configurations and the goals they can achieve, this paper contributes an automated model-based reasoning approach using view generations. Our approach allows for exploring which goals can be fulfilled by which configurations and which goals cannot be fulfilled by these configurations. We evaluated the approach using an industrial case study which shows the applicability of the approach and a controlled experiment which shows the benefits of the approach.