Exploiting Memory-Boundedness in Energy-Efficient Hard Real-Time Scheduling

Dynamic voltage and frequency scaling (DVFS) has been extensively exploited in the context of hard real-time systems for the development of energy efficient task scheduling algorithms. However, when tasks are memory bounded, further energy improvement could be obtained. In this paper we analyze the effect of memory boundedness in a state-of-the-art energy efficient hard real-time scheduling algorithm, and we propose a new technique to take into account these effects to substantially improve energy efficiency of the scheduling algorithm while still preventing deadline misses. The proposed technique is compared to a state-of-the-art hard real-time scheduling algorithm from energy efficiency viewpoint. Results show an energy reduction from 15% to 90% depending on the amount of memory boundedness of the task.