Keywords
wearable devices, heterogeneous multicore system, big.LITTLE architecture, task scheduling
Abstract
The rapid development of wearable computing technologies has led to an increased involvement of wearable devices in the daily lives of people. The main power sources of wearable devices are batteries; so, researchers must ensure high performance while reducing power consumption and improving the battery life of wearable devices. The purpose of this study is to analyze the new features of an Energy-Aware Scheduler (EAS) in the Android 7.1.2 operating system and the scarcity of EAS schedulers in wearable application scenarios. Also, the paper proposed an optimization scheme of EAS scheduler for wearable applications (Wearable-Application-optimized Energy-Aware Scheduler (WAEAS). This scheme improves the accuracy of task workload prediction, the energy efficiency of central processing unit core selection, and the load balancing. The experimental results presented in this paper have verified the effectiveness of a WAEAS scheduler.
Publisher
Tsinghua University Press
Recommended Citation
Zhan Zhang, Xiang Cong, Wei Feng et al. WAEAS: An Optimization Scheme of EAS Scheduler for Wearable Applications. Tsinghua Science and Technology 2021, 26(1): 72-84.
