Verifying network performance of cyber-physical systems with multiple runtime configurations

Modern Cyber-Physical Systems (CPS) must increasingly adapt to changing contexts, like smart cars to changing driving conditions. Thus, design approaches are facing a rapidly growing number of network runtime configurations. With recent approaches this problem can be solved for design space exploration (DSE) by analyzing the network performance of single configurations which are intended to represent the entire runtime variability space. This technique can be applied for DSE since the latter only intends to find an optimized system setup. Yet it does not meet the requirements of network verification, since it does not necessarily find the worst-case for all applications. To solve this, we developed an integrated model, which allows describing runtime variability in the network performance model with a0-1 linear-fractional program. Thus, we can cover entire runtime variability spaces without analyzing every single network runtime configuration. Although the approach utilizes heuristics, it still guarantees worst-case results. We can show that in comparison to state-of-the-art methods our approach scales for large automotive systems with multiple network configurations. Moreover, our evaluation results highlight the superior capabilities of our method with respect to accuracy and computation time.