Accurate online power estimation and automatic battery behavior based power model generation for smartphones

Lide Zhang, B. Tiwana, Zhiyun Qian, Zhaoguang Wang, R. Dick, Z. Morley Mao, Lei Yang
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引用次数: 1239

Abstract

This paper describes PowerBooter, an automated power model construction technique that uses built-in battery voltage sensors and knowledge of battery discharge behavior to monitor power consumption while explicitly controlling the power management and activity states of individual components. It requires no external measurement equipment. We also describe PowerTutor, a component power management and activity state introspection based tool that uses the model generated by PowerBooter for online power estimation. PowerBooter is intended to make it quick and easy for application developers and end users to generate power models for new smartphone variants, which each have different power consumption properties and therefore require different power models. PowerTutor is intended to ease the design and selection of power efficient software for embedded systems. Combined, PowerBooter and PowerTutor have the goal of opening power modeling and analysis for more smartphone variants and their users.
智能手机准确的在线功率估计和基于电池行为的自动功率模型生成
本文介绍了PowerBooter,一种自动化的电源模型构建技术,它使用内置的电池电压传感器和电池放电行为的知识来监测功耗,同时显式地控制各个组件的电源管理和活动状态。它不需要外部测量设备。我们还描述了PowerTutor,一个基于组件电源管理和活动状态自省的工具,它使用PowerBooter生成的模型进行在线功率估计。PowerBooter旨在使应用程序开发人员和最终用户能够快速轻松地为新的智能手机变体生成功率模型,每种智能手机都具有不同的功耗属性,因此需要不同的功率模型。PowerTutor旨在简化嵌入式系统中节能软件的设计和选择。结合起来,PowerBooter和PowerTutor的目标是为更多的智能手机变体及其用户开放功率建模和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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