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HEALERS: a heterogeneous energy-aware low-overhead real-time scheduler
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Journal Article
HEALERS: a heterogeneous energy-aware low-overhead real-time scheduler
2019
Overview
Devising energy-efficient scheduling strategies for real-time periodic tasks on heterogeneous platforms is a challenging as well as a computationally demanding problem. This study proposes a low-overhead heuristic strategy called, HEALERS, for dynamic voltage and frequency scaling (DVFS)-cum-dynamic power management (DPM) enabled energy-aware scheduling of a set of periodic tasks executing on a heterogeneous multi-core system. The presented strategy first applies deadline-partitioning to acquire a set of distinct time-slices. At any time-slice boundary, the following three-phase operations are applied to obtain a schedule for the next time-slice: first, it computes the fragments of the execution demands of all tasks onto each of the different processing cores in the platform. Next, it generates a schedule for each task on one or more processing cores such that the total execution demand of all tasks is satisfied. Finally, HEALERS applies DVFS and DPM on all processing cores so that energy consumption within the time-slice may be minimized while not jeopardising execution requirements of the scheduled tasks. Experimental results show that the proposed scheme is not only able to achieve appreciable energy savings with respect to state-of-the-art (5–42% on average) but also enables a significant improvement in resource utilisation (as high as 58%).
Publisher
The Institution of Engineering and Technology,John Wiley & Sons, Inc
Subject
/ DPM
/ DVFS
/ dynamic voltage and frequency scaling
/ energy‐efficient scheduling strategies
/ HEALERS
/ heterogeneous energy‐aware real‐time scheduler
/ heterogeneous multicore system
/ low‐overhead heuristic strategy
/ real‐time energy‐aware scheduling techniques
/ Special Issue: Energy-efficient Computing for Embedded and IoT Devices
