Leakage-Aware Reallocation for Periodic Real-Time Tasks on Multicore Processors
Hongtao Huang, Feng Xia, Jijie Wang, Siyu Lei, Guowei Wu

TL;DR
This paper proposes a leakage-aware reallocation method for periodic real-time tasks on multicore processors, combining static scheduling with runtime task reallocation to significantly reduce energy consumption.
Contribution
It introduces a novel runtime task reallocation technique that aggregates idle times to maximize core sleep states, improving energy efficiency beyond existing DVS methods.
Findings
Up to 20% energy savings demonstrated in simulations
Effective reduction of leakage and dynamic energy consumption
Enhanced energy efficiency with minimal performance impact
Abstract
It is an increasingly important issue to reduce the energy consumption of computing systems. In this paper, we consider partition based energy-aware scheduling of periodic real-time tasks on multicore processors. The scheduling exploits dynamic voltage scaling (DVS) and core sleep scheduling to reduce both dynamic and leakage energy consumption. If the overhead of core state switching is non-negligible, however, the performance of this scheduling strategy in terms of energy efficiency might degrade. To achieve further energy saving, we extend the static task scheduling with run-time task reallocation. The basic idea is to aggregate idle time among cores so that as many cores as possible could be put into sleep in a way that the overall energy consumption is reduced. Simulation results show that the proposed approach results in up to 20% energy saving over traditional leakage-aware DVS.
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