Education Class 1
Session: EC1
Educator: Jian-Jia Chen
Institute: TU Dortmund
Time & Date: September 14, 2023, 10:00 – 12:00 CET
Title: Data Flow from Cause to Effect in Distributed Systems: Data Age and Reaction
Abstract: Cyber-physical real-time systems are information processing systems that require both functional as well as timing correctness and have interactions with the physical world. In many applications of cyber-physical systems, a sequence of tasks is necessary to perform a certain functionality. For example, from a sensor to an actuator, the first task reads the sensor value (cause), the second task processes the data, and the third task produces an output for the actuator (an effect is triggered). The data dependency between such tasks can be described by the data flow of a cause-effect chain. This education class provides the historical perspectives and the state-of-the-art analyses to safely bound the *end-to-end* timing properties of such cause-effect chains regarding the reaction time (how fast can a reaction be in the worst case) and the data age (how old is the data source of an actuation in the worst case). We will cover also examples on how to extend the results to deal with data flows in Robot Operating Systems (ROS) 2. This class provides a unique opportunity for those who are interested in applying results from classical real-time systems to deal with a new class of timing properties in distributed systems where *data freshness* plays an important role.
