Ajou University repository

Phase-based predicting the battery remaining time for Android mobile devices
Citations

SCOPUS

1

Citation Export

DC Field Value Language
dc.contributor.authorOhk, Seung Ryeol-
dc.contributor.authorHong, Seok Min-
dc.contributor.authorKim, Young Jin-
dc.date.issued2021-01-01-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/36700-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122944606&origin=inward-
dc.description.abstractSince 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.-
dc.description.sponsorshipACKNOWLEDGMENT 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)-
dc.language.isoeng-
dc.publisherIEEE Computer Society-
dc.subject.meshAndroid-
dc.subject.meshBattery capacity-
dc.subject.meshBattery consumption-
dc.subject.meshBattery remaining time-
dc.subject.meshLow power techniques-
dc.subject.meshPhase-
dc.subject.meshPhase based-
dc.subject.meshPower-
dc.subject.meshPower estimations-
dc.subject.meshSmart phones-
dc.titlePhase-based predicting the battery remaining time for Android mobile devices-
dc.typeConference-
dc.citation.conferenceDate2021.10.20. ~ 2021.10.22.-
dc.citation.conferenceName12th International Conference on Information and Communication Technology Convergence, ICTC 2021-
dc.citation.editionICTC 2021 - 12th International Conference on ICT Convergence: Beyond the Pandemic Era with ICT Convergence Innovation-
dc.citation.endPage944-
dc.citation.startPage942-
dc.citation.titleInternational Conference on ICT Convergence-
dc.citation.volume2021-October-
dc.identifier.bibliographicCitationInternational Conference on ICT Convergence, Vol.2021-October, pp.942-944-
dc.identifier.doi10.1109/ictc52510.2021.9621027-
dc.identifier.scopusid2-s2.0-85122944606-
dc.identifier.urlhttp://ieeexplore.ieee.org/xpl/conferences.jsp-
dc.subject.keywordAndroid-
dc.subject.keywordbattery remaining time-
dc.subject.keywordmobile device-
dc.subject.keywordphase-
dc.subject.keywordpower estimation-
dc.subject.keywordsmartphone-
dc.type.otherConference Paper-
dc.description.isoafalse-
dc.subject.subareaInformation Systems-
dc.subject.subareaComputer Networks and Communications-
Show simple item record

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Kim, Young-Jin  Image
Kim, Young-Jin 김영진
Department of Electrical and Computer Engineering
Read More

Total Views & Downloads

File Download

  • There are no files associated with this item.