EMR: Removing Multicollinear Event Monitors to Improve Timing Modelling of Real-Time Systems

Multicollinearity of Event Monitors (EMs) negatively impacts the modeling of non-functional critical metrics in real-time systems like worst-case timing and energy usage since some EMs are over-represented and can reduce model accuracy. To address this challenge, we propose Event Monitor Reduction (EMR), a method to select a reduced set of non-related (independent) features (EMs), hence eliminating multicollinearity. In particular, EMR finds linear relations between the EMs and removes dependent ones without data loss. EMR does not create new features like Principal Component Analysis does, simplifying interpretability. Results on synthetic data and data collected from the execution of representative benchmarks on an avionicsgrade processor show the benefits of our method in removing multicollinear EMs. We further illustrate the benefits of EMR on two different multicore timing contention models, showing how its application helps to reduce execution time requirements and increase the accuracy of the models.