Practical Energy-Aware Scheduling for Real-Time Multiprocessor Systems

Energy-aware real-time multiprocessor scheduling has been studied extensively so far. However, some of the constraints associated with the practical DVS applications have been ignored for simplicity. These constraints include discrete speed, idle power, inefficient speed, and application-specific power characteristics etc. This work targets energy-aware scheduling of periodic real-time tasks on the DVS-equipped multiprocessor systems with practical constraints. An adaptive minimal bound first-fit (AMBFF) algorithm with consideration of these realistic constraints is proposed for both dynamic-priority and fixed-priority multiprocessor scheduling. Simulation results on three commercial processor models show that our algorithm can save significantly more energy than existing algorithms.