Yesterday, Bruno Dzikowski successfully defended his master’s thesis titled “Practical Recommendations for Accurately Predicting Performance Degradation Caused by Memory Contention” The thesis addresses the challenge of predicting performance in microservice-based architectures for cyber-physical systems (CPS) running on multi-core platforms, where resource contention significantly impacts accuracy. Existing methods model interference sensitivity and contentiousness but lack practical implementation guidelines.
Bruno’s work introduces a compositional performance prediction framework with three key contributions: 1) a validated contentiousness profiling component, 2) an analysis of how system configuration affects prediction accuracy, and 3) the design and implementation of an experimental testbed. Tested across 195 co-location scenarios, the approach achieves high accuracy (median error ≈ 1.4%), demonstrating its effectiveness for forecasting microservice performance.
We are very proud of the excellent research Bruno conducted during his internship with TNO-ESI, which resulted in an outstanding thesis that was confidently presented and defended. We thanks Bruno for the excellent collaboration and wish him all the best for his future career.
