[1]程茹洁,陆 建,蒋厚明,等.智能移动终端的能耗模型研究[J].计算机技术与发展,2017,27(12):128-132.[doi:10.3969/ j. issn.1673-629X.2017.12.028]
　CHENG Ru-jie,LU Jian,JIANG Hou-ming,et al.Research on Energy Consumption Model on Smartphones[J].Computer Technology and Development,2017,27(12):128-132.[doi:10.3969/ j. issn.1673-629X.2017.12.028]
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智能移动终端的能耗模型研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年12期
页码:
128-132
栏目:
安全与防范
出版日期:
2017-12-10

文章信息/Info

Title:
Research on Energy Consumption Model on Smartphones
文章编号:
1673-629X(2017)12-0128-05
作者:
程茹洁1 ; 陆 建1 ; 蒋厚明2 ; 胡 牧2
1. 东南大学 信息科学与工程学院,江苏 南京 210096;
2. 国网电力科学研究院,江苏 南京 211000
Author(s):
CHENG Ru-jie 1 ; LU Jian 1 ; JIANG Hou-ming 2 ; HU Mu 2
1. School of Information Science and Engineering,Southeast University,Nanjing 210096,China;
2. State Grid Electric Power Research Institute,Nanjing 211000,China
关键词:
智能移动终端; 安卓系统; 场景测试; 功耗模型; CPU; 反馈调节
Keywords:
mobile phone; Android System; scenario test; power consumption model; feedback regulation
分类号:
TP31
DOI:
10.3969/ j. issn.1673-629X.2017.12.028
文献标志码:
A
摘要:
为分析智能手机的实时能耗,定位手机的高能耗组件,帮助用户了解手机的能耗去向,并针对性地采取节能措施,从华为手机 Y518-T00 入手,开发了一款基于安卓系统的应用。 针对重要硬件组件(CPU、屏幕、Wi-Fi 接口、音频、GPS),通过场景测试收集的数据进行拟合分析,构建了每个硬件组件对应的能耗模型,进一步得到了整机的能耗模型。 针对CPU,提出了一种反馈调节的模式来控制其占用率,有效地测量出 CPU 在不同占用率和频率下的能耗特点,消除了 CPU 的运行给其他组件能耗分析带来的影响。 最后,用常见的两款手机应用进行了测试。 结果表明,该能耗模型的相对误差均低于 7%,具有较好的精度,可用于了解手机能耗在硬件组件的分布情况。
Abstract:
To analyze the real-time energy consumption for mobile phone,find the mobile phone components with high energy consumption,and help users understand where the energy goes so as to adopt relevant energy-saving measures,an application based on Android is developed from Huawei Y518-T00. For the important hardware components such as CPU,display,Wi-Fi interface,audio and GPS,the data collected by scenario test is analyzed,and the energy consumption models are established for each component respectively to further
construct the energy consumption model of mobile phone. A feedback-regulation method is presented to control the utilization of CPU,based on which the power characteristics of CPU under different utilizations and frequency are measured and the impact of CPU running on energy analysis of other components is eliminated. At last,the two popular apps are tested. Experiment shows that the relative error of the proposed model is less than 7%,with better accuracy,and it helps users understand the energy distribution of hardware components on phones.

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　YUAN Zhi-jian[],WANG Chun-ping[],CHEN Rong[],et al.Security Threats on Android Platform and Their Coping Strategies[J].Computer Technology and Development,2013,(12):110.
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更新日期/Last Update: 2018-03-07