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Open Access

WAEAS: An Optimization Scheme of EAS Scheduler for Wearable Applications

School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Beijing Information Technology Institute, Beijing 100192, China.
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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.

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Tsinghua Science and Technology
Pages 72-84

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Cite this article:
Zhang Z, Cong X, Feng W, et al. WAEAS: An Optimization Scheme of EAS Scheduler for Wearable Applications. Tsinghua Science and Technology, 2021, 26(1): 72-84. https://doi.org/10.26599/TST.2019.9010040

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Received: 24 May 2019
Accepted: 27 August 2019
Published: 19 June 2020
© The author(s) 2021.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).