Today, Jan Przystal presented his literature study Performance Prediction for Microservice-Based Cyber-Physical Systems: A Cross-Domain Literature Review. The study reviews existing methods for predicting performance in Cyber-Physical Systems (CPS) during the early design phase. It focuses on how resource contention, caused by shared hardware such as caches, memory, and I/O, leads to performance degradation, and why this makes Design Space Exploration (DSE) challenging for complex distributed CPS. The study surveys simulation-based approaches, profiling techniques, and interference prediction methods originating from both CPS and cloud computing, and evaluates their suitability for fast and scalable performance estimation. It concludes that while current methods can provide useful approximations, none fully meet the need for a quick, accurate, and scalable prediction approach for large CPS design spaces, highlighting the need for further research in this area. These are challenges that Jan will address during his master project, building on our earlier work with Bruno Dzikowski in this area.
It was nice to see that there was broad interest in Jan’s presentation not only from the performance team at TNO-ESI, but also among some of its industry partners, as well as experts in performance prediction from University of Amsterdam, Eindhoven University of Technology, and University of Twente. That certainly made the Q&A session afterwards spicier, although Jan confidently answered most of the questions. Congratulations Jan on work well done!
