HEART: A Heterogeneous Energy-Aware Real-Time scheduler

Devising energy efficient scheduling strategies for real-time periodic tasks on heterogeneous platforms is a challenging as well as a computationally demanding problem. As a consequence, today we face a scarcity of low-overhead realtime energy aware scheduling techniques which are applicable to heterogeneous platforms. Hence, this paper proposes a low-overhead heuristic approach called, HEART, for DVFS enabled energy-aware scheduling of a set of periodic tasks executing on a heterogeneous multi-core system. The proposed approach first applies deadline partitioning scheme to obtain a set of distinct time-slices. For each such time-slice, HEART conducts the following three phase operation: First, it computes the fragments of the execution demands of all tasks on different processing cores of the platform. Next, it generates a schedule of each task on one or more processing cores such that total execution demands of all tasks are satisfied. Finally, HEART applies DVFS on all processing cores to minimise the energy consumed by the system. Experimental studies show that our scheme is able to significantly improve acceptance ratios for task sets, and energy savings of the platform, compared to the state-of-the-art.