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Frequency-independent smartphone peripherals energy consumption estimation. / Сартасов, Станислав Юрьевич; Мирошников, Владислав Игоревич; Кузнецов, Илья Александрович.

In: Cybernetics and Physics, Vol. 12, No. 1, 30.06.2023, p. 42-50.

Research output: Contribution to journal › Article › peer-review

Harvard

Сартасов, СЮ, Мирошников, ВИ & Кузнецов, ИА 2023, 'Frequency-independent smartphone peripherals energy consumption estimation', Cybernetics and Physics, vol. 12, no. 1, pp. 42-50. https://doi.org/10.35470/2226-4116-2023-12-1-42-50

APA

Сартасов, С. Ю., Мирошников, В. И., & Кузнецов, И. А. (2023). Frequency-independent smartphone peripherals energy consumption estimation. Cybernetics and Physics, 12(1), 42-50. https://doi.org/10.35470/2226-4116-2023-12-1-42-50

Vancouver

Сартасов СЮ, Мирошников ВИ, Кузнецов ИА. Frequency-independent smartphone peripherals energy consumption estimation. Cybernetics and Physics. 2023 Jun 30;12(1):42-50. https://doi.org/10.35470/2226-4116-2023-12-1-42-50

Author

Сартасов, Станислав Юрьевич ; Мирошников, Владислав Игоревич ; Кузнецов, Илья Александрович. / Frequency-independent smartphone peripherals energy consumption estimation. In: Cybernetics and Physics. 2023 ; Vol. 12, No. 1. pp. 42-50.

BibTeX

@article{74e40bdf3a254ec583a6a482a0038505,
title = "Frequency-independent smartphone peripherals energy consumption estimation",
abstract = "The power consumption of mobile devices is a hot topic these days, and it is important to address it when developing applications. One of the most popular ways to measure it is accessing internal sensors using Android Debug Bridge (ADB). We discovered that measurement frequency may skew the power readings. Based on this approach we propose our own algorithm for calculating smartphone energy consumption constants — the power in milliamperes at nominal voltage for different peripherals states. Our algorithm takes measurement frequency bias into account, and its results are compared with the method previously published in literature as well as the baseline data from power profile. We conclude that the developed approach provides better estimation.",
keywords = "Android, Power Profile, Energy Consumption, Power Constants, Wi-Fi, Bluetooth",
author = "Сартасов, {Станислав Юрьевич} and Мирошников, {Владислав Игоревич} and Кузнецов, {Илья Александрович}",
year = "2023",
month = jun,
day = "30",
doi = "10.35470/2226-4116-2023-12-1-42-50",
language = "English",
volume = "12",
pages = "42--50",
journal = "Cybernetics and Physics",
issn = "2223-7038",
publisher = "IPACS",
number = "1",

}

RIS

TY - JOUR

T1 - Frequency-independent smartphone peripherals energy consumption estimation

AU - Сартасов, Станислав Юрьевич

AU - Мирошников, Владислав Игоревич

AU - Кузнецов, Илья Александрович

PY - 2023/6/30

Y1 - 2023/6/30

N2 - The power consumption of mobile devices is a hot topic these days, and it is important to address it when developing applications. One of the most popular ways to measure it is accessing internal sensors using Android Debug Bridge (ADB). We discovered that measurement frequency may skew the power readings. Based on this approach we propose our own algorithm for calculating smartphone energy consumption constants — the power in milliamperes at nominal voltage for different peripherals states. Our algorithm takes measurement frequency bias into account, and its results are compared with the method previously published in literature as well as the baseline data from power profile. We conclude that the developed approach provides better estimation.

AB - The power consumption of mobile devices is a hot topic these days, and it is important to address it when developing applications. One of the most popular ways to measure it is accessing internal sensors using Android Debug Bridge (ADB). We discovered that measurement frequency may skew the power readings. Based on this approach we propose our own algorithm for calculating smartphone energy consumption constants — the power in milliamperes at nominal voltage for different peripherals states. Our algorithm takes measurement frequency bias into account, and its results are compared with the method previously published in literature as well as the baseline data from power profile. We conclude that the developed approach provides better estimation.

KW - Android

KW - Power Profile

KW - Energy Consumption

KW - Power Constants

KW - Wi-Fi

KW - Bluetooth

UR - https://www.mendeley.com/catalogue/696f34c5-e62a-31bd-9d61-0761992411e7/

U2 - 10.35470/2226-4116-2023-12-1-42-50

DO - 10.35470/2226-4116-2023-12-1-42-50

M3 - Article

VL - 12

SP - 42

EP - 50

JO - Cybernetics and Physics

JF - Cybernetics and Physics

SN - 2223-7038

IS - 1

ER -

ID: 106919442