Applying the peak over thresholds method on worst-case response time analysis of complex real-time systems

The predictability of timing behavior is a very important performance issue of a real-time system. As the complexity of modern industrial systems increases, analyzing the timing behaviors of those systems becomes more and more challenging. Most of the existing analysis methods depend on static and detailed information of the systems under analysis. However, sometimes only partial information of a system can be available, or it may require too much effort on obtaining those details, making those analysis methods much less feasible. Moreover, those methods usually focus on some specific system models with unrealistic assumptions, consequently, applying those methods on a complex industrial real-time system may result in overly pessimistic results. Therefore, in this paper, we propose a statistical method to compute Worst-Case Response Times (WCRTs) of complex real-time systems regarding soft timing constraints, which can provide a higher general applicability with less required system information. Our approach employs a Peak Over Thresholds (POT) method, which is a branch of the Extreme Value Theory (EVT). For the evaluation, we have applied this approach on the analysis of message transmission latencies over Controller Area Networks (CAN).