Congratulations to the newly minted Dr. Panagiotis (Panos) Giannakopoulos, who has successfully defended his dissertation, “Predictable Application Performance in Resource Clusters” The dissertation tackles the challenge of meeting strict Round-Trip Time (RTT) deadlines for time-sensitive applications in heterogeneous, resource-constrained edge environments by developing lightweight, accurate performance predictors. These predictors leverage selected system metrics and machine learning models to anticipate execution time and variability, enabling proactive scheduling and load balancing that improve efficiency and reduce resource waste, with demonstrated success on Electron Microscopy workloads in Kubernetes-based clusters.
This research was conducted as part of the NWO ADAPTOR project, co-funded by Thermo Fisher Scientific and ASTRON. I have had the pleasure of serving on the user committee for this project over the past couple of years and was honored to be invited to join the Ph.D. committee. Over the years, Panos has presented his work at TNO-ESI several times in various settings and was also invited to share his insights at Thales. Panos will now continue his work as a postdoctoral researcher at TU/e.
