Worst-Case Cause-Effect Reaction Latency In Systems With Non-Blocking Communication

In real-time embedded systems, a system functionality is often implemented using a data-flow chain over a set of communicating tasks. A critical non-functional requirement in such systems is to restrict the amount of time, i.e. cause-effect latency, for an input to impact its corresponding output. The problem of estimating the worst-case cause-effect latency is well-studied in the context of blocking inter-task communication. Recent research results show that non-blocking communication preserving functional semantics is critical for the model-based design of dynamically updatable systems. In this paper, we study the worst-case cause-effect reaction latency estimation problem in the context of non-blocking inter-task communication. We present a computationally efficient algorithm that tightly over-approximates the exact worst-case reaction latency in cause-effect data-flow chains.