用于移动应用的轻量级在线电源监测和控制

Bo Wang, Xinghui Zhao, David Chiu
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引用次数: 3

摘要

长期以来,有限的电池电量一直是移动应用程序面临的挑战。因此,电力监测与管理工作引起了人们极大的兴趣。在本文中,我们提出了一个模型来估计移动应用程序在运行时的功耗,基于特定于应用程序的每动作功率分析。此外,我们还开发了在线优化技术,帮助最大限度地提高用户体验,同时节省电力。我们的power模型轻量级且灵活,因为它可以被任何移动应用程序作为插件使用,并且它可以支持用户定义的优化机制。通过对某移动应用程序的现场研究,对该方法进行了评估,实验结果表明,该模型能够准确地捕获应用程序的功耗,并可根据用户需求对功耗进行优化。
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Lightweight online power monitoring and control for mobile applications
Limited battery power has long been a challenge for mobile applications. As a result, the work in power monitoring and management has attracted great interests. In this paper, we propose a model to estimate power consumption of mobile applications at run-time, based on application-specific per-action power profiling. In addition, we have developed on-line optimization techniques which help maximize users' experience while conserving power. Our power model is lightweight and flexible, in that it can be used by any mobile applications as a plugin, and it can support user-defined optimization mechanisms. This approach has been evaluated using a case study, a mobile application for field studies, and the experimental results show that our model accurately captures power consumption of the application, and the model can be used to optimize the power consumption based on users' needs.
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