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Phase-based predicting the battery remaining time for Android mobile devices
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Publication Year
2021-01-01
Journal
International Conference on ICT Convergence
Publisher
IEEE Computer Society
Citation
International Conference on ICT Convergence, Vol.2021-October, pp.942-944
Keyword
Androidbattery remaining timemobile devicephasepower estimationsmartphone
Mesh Keyword
AndroidBattery capacityBattery consumptionBattery remaining timeLow power techniquesPhasePhase basedPowerPower estimationsSmart phones
All Science Classification Codes (ASJC)
Information SystemsComputer Networks and Communications
Abstract
Since smartphones are battery-driven, it is important to know how power-efficiently and how long they are used in a limited battery capacity. As smartphones become popular and their usage time increases, many low-power techniques have been studied to use smartphones' batteries efficiently. However, most low-power techniques are only interested in techniques that reduce power purely, and do not care about the feasible time of the current workload based on the battery remaining time. In this paper, we propose a method to predict the accurate power consumption of recent smartphones for development of efficient low power techniques. Our method estimates the battery remaining time to predict the viable time of the running workload with the remaining smartphone battery. In detail, it predicts the overall power consumption for a smartphone by using power models for a CPU, a GPU, and a display that have a high proportion of energy consumption in smartphones. Through experiments, we build a prediction model that calculates battery consumption by using the predicted power consumption according to CPU/GPU phase of the workload used in the experiment. Consequently, we complete a technique to predict battery consumption and remaining time for arbitrary workloads.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36700
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122944606&origin=inward
DOI
https://doi.org/10.1109/ictc52510.2021.9621027
Journal URL
http://ieeexplore.ieee.org/xpl/conferences.jsp
Type
Conference
Funding
ACKNOWLEDGMENT This work has been supported by the Future Combat System Network Technology Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.(UD109 033ED)
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Kim, Young-Jin 김영진
Department of Electrical and Computer Engineering
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