Empirical quantification of pessimism in state-of-the-art scheduling theory techniques for periodic and sporadic DRE tasks

Distributed, Real-time, Embedded (DRE) systems present numerous challenges with respect to certification of their real-time behavior. Ideally, to address these we would like to build a model of our system that captures relevant information about end to end real-time requirements, resource consumptions requirements and resource availability, and subject the model to real-time scheduling analysis to predict performance. Presently, scheduling theory techniques have seen limited application in DRE systems for multiple reasons including pessimistic predictions of worst-case response times. Our study quantifies the pessimism in the predictions of worst-case response times of competing end-to-end distributed periodic tasks by comparing values observed in simulation with values computed using multiple scheduling theory techniques. Specifically we consider nongreedy synchronization protocols for tasks with a high degree of recurrence. Our results show that for an end-to-end task model nongreedy techniques, when used with proportional deadline monotonic scheduling, reduce the pessimism in worst-case response time predictions to within 5% of the actual value in over 90% of cases. These (quasi) static techniques represent a baseline against which we can evaluate emerging, control theoretic, adaptive scheduling methods.