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Online latency monitoring of time-sensitive event chains in ROS2

Highly-automated driving involves chains of perception, decision, and control functions. These functions involve dataintensive algorithms that motivate the use of a data-centric middleware and a service-oriented architecture. As an example, we use the open-source project Autoware.Auto, which bases on the Robot Operating System (ROS) 2. Often, function chains define a safety-critical automated control task with weakly-hard real-time constraints. Providing the required assurance by formal analysis, however, is challenged by the complex hardware/software structure of these systems. We therefore propose an approach
that combines measurement, suitable distribution of deadlines, and application-level online monitoring that serves to supervise the execution of service-oriented software systems with multiple function chains and weakly-hard real-time constraints. We further evaluate our proof-of-concept implementation in ROS2 on
an environment perception use case from Autoware.Auto.

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