EA-HRT: An Energy-Aware scheduler for Heterogeneous Real-Time systems

Abstract

Developing energy-efficient schedulers for real-time heterogeneous platforms executing periodic tasks is an onerous as well as a computationally challenging issue. This research presents a heuristic strategy named, EA-HRT, for DVFS based energy-aware scheduling of a set of periodic tasks executing on a heterogeneous multicore platform. Initially it calculates the execution demands of every task on each of the different type of cores. Then, it simultaneously allocates each task on available cores and selects operating frequencies for the concerned cores such that the summation of execution demands of all tasks are met as well as there is minimum change in energy consumption for the system. Experimental results show that our proposed strategy is not only able to achieve appreciable energy savings with respect to state-of-the-art (2% to 37% on average) but also enables significant improvement in resource utilization (as high as 57%).