Probabilistic preemption control using frequency scaling for sporadic real-time tasks

Abstract

Preemption related costs are major sources of unpredictability in the task execution times in a real-time system. We examine the possibility of using CPU frequency scaling to control the preemption behavior of real-time sporadic tasks scheduled using a preemptive Fixed Priority Scheduling (FPS) policy. Our combined offline-online method provides probabilistic preemption control guarantees by making use of the release time probabilities of the sporadic tasks. The offline phase derives the probability related deviation from the minimum inter-arrival time of tasks. The online algorithm uses this information to calculate appropriate CPU frequencies that guarantees non-preemptive task executions while preserving the overall system schedulability. The online algorithm has a linear complexity and does not lead to significant implementation overheads. Our evaluations demonstrate the effectiveness of the method as well as the possibility of energy-preemption trade offs. Even though we have considered FPS, our method can easily be extended to dynamic priority scheduling schemes.