A novel energy-oriented EDF scheduler that changes the task execution order to better utilize slack time to decrease energy consumption, while meeting
Energy is a major concern when designing real-time systems. A common method for saving energy while still guaranteeing the real-time constraints is to embed dynamic voltage and frequency scaling (DVFS) mechanisms and dynamic power management (DPM) mechanisms within a real-time scheduling algorithm such as EDF. This paper proposes a new extension to the EDF scheduler, termed energy oriented EDF (EO-EDF). The new scheduler makes it possible to change the original EDF task execution order to better utilise the slack time and thus decrease the energy consumption, while still meeting the task deadlines. The new task order is defined according to a novel criterion we invented, termed task prediction order (TPO). The paper introduces two new versions of the EO-EDF scheduler, termed TPO-EDF and STPO-EDF. While STPO-EDF applies the TPO criterion in a static manner, TPO-EDF allows it to be used dynamically. We simulate the new proposed algorithms using both synthetic workloads and real-time benchmarks. The evaluations show that integrating both the TPO-EDF and STPO-EDF scheduling algorithms with DVFS and DPM mechanisms achieves an energy savings of 30% on average, in comparison with current known EDF based scheduling utilising DVFS and DPM mechanisms.