Accurate prediction of available battery time for mobile applications

Dongwon Kim, Yohan Chon, Wonwoo Jung, Yungeun Kim, Hojung Cha

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Energy consumption in mobile devices is an important issue for both system developers and users. Users are aware of the battery-related information of their mobile devices and tend to take appropriate actions to increase the battery life. In this article, we propose a framework that accurately estimates the remaining battery time of applications at runtime. The framework profiles the power behavior of applications tied with activated hardware components and estimates the remaining battery budget utilizing the battery-related data provided by the device. The experiments validate that our method predicts the remaining battery time for applications with approximately 93% of accuracy.

Original languageEnglish
Article number48
JournalACM Transactions on Embedded Computing Systems
Volume15
Issue number3
DOIs
Publication statusPublished - 2016 May

Fingerprint

Mobile devices
Energy utilization
Hardware
Experiments

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture

Cite this

Kim, Dongwon ; Chon, Yohan ; Jung, Wonwoo ; Kim, Yungeun ; Cha, Hojung. / Accurate prediction of available battery time for mobile applications. In: ACM Transactions on Embedded Computing Systems. 2016 ; Vol. 15, No. 3.
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Accurate prediction of available battery time for mobile applications. / Kim, Dongwon; Chon, Yohan; Jung, Wonwoo; Kim, Yungeun; Cha, Hojung.

In: ACM Transactions on Embedded Computing Systems, Vol. 15, No. 3, 48, 05.2016.

Research output: Contribution to journalArticle

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