Model-based Performance Analysis for Architecting Cyber-Physical Dynamic Spaces

Architecting Cyber-Physical Systems is not trivial since their intrinsic nature of mixing software and hardware components poses several challenges, especially when the physical space is subject to dynamic changes, e.g., paths of robots suddenly not feasible due to objects occupying transit areas or doors being closed with a high probability. This paper provides a quantitative evaluation of different architectural patterns that can be used for cyber-physical systems to understand which patterns are more suitable under some peculiar characteristics of dynamic spaces, e.g., frequency of obstacles in paths. We use stochastic performance models to evaluate architectural patterns, and we specify the dynamic aspects of the physical space as probability values. This way, we aim to support software architects with quantitative results indicating how different design patterns affect some metrics of interest, e.g., the system response time. Experiments show that there is no unique architectural pattern suitable to cope with all the dynamic characteristics of physical spaces. Each architecture differently contributes when varying the physical space, and it is indeed beneficial to switch among multiple patterns for an optimal solution.