Rating Google-Play Apps' Energy Consumption on Android Smartphones

Almasri, Abdullah; Sameh, Ahmed

doi:10.1109/menacomm46666.2019.8988554

Cited by 3 publications

(2 citation statements)

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“…One of the first problems likely to be encountered in seeking to evaluate energy waste through irresponsible smartphone use, is that in the words of Pärssinen in [3] "there are no commonly agreed ways to assess … total energy consumption". Multiple factors are likely to contribute to energy waste through smartphone use, including but not limited to, overcharging or continuous unnecessary recharging [4]; using cheap nonbranded charges whose energy usage can be anything up to 20 times that of branded or recommended chargers [5]; having an excessive number of apps open at any one time [6]; failing to timeout screens during non-use [6]; playing videos purely for the purposes of listening and not watching [7]; and keeping unnecessary apps open, e.g. location services, when not in use [8].…”

Section: Relevant Literaturementioning

confidence: 99%

Estimating the Cost of Wasted Energy During Overcharging Smartphones and Using COVID19 Apps

Almasri

Gouveia

Fernandes

2022

Int. J. Interact. Mob. Technol.

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Energy wastage through irresponsible smartphone use comprises a significant sum. Using a secondary desk-based literature review, this paper evaluates con-temporary literature to calculate an approximate estimate of the amount of energy wasted through irresponsible smartphone use by US users on an annual basis. Conservative estimates purely based on overcharging of smartphones in the US suggest that the figure is in excess of US$400m per annum. A variety of factors contribute to irresponsible smartphone use, which are predominantly behavioral in nature. This paper highlights some of the impacts of excessive smartphone use and considers steps which might be taken by users themselves to reduce energy wastage during smartphone use. In addition, suggestions are made to manufac-turers to help them ‘nudge’ users into more responsible behavior through the principles of behavioral economics.

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Section: Relevant Literaturementioning

confidence: 99%

Estimating the Cost of Wasted Energy During Overcharging Smartphones and Using COVID19 Apps

Almasri

Gouveia

Fernandes

2022

Int. J. Interact. Mob. Technol.

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“…However, most intelligent mobile terminals currently are powered by energy-limited batteries. Although a lot of optimization has been carried out at the battery level, hardware components, and operating system levels to improve energy utilization efficiency [3,4], these improvements still cannot prevent low energy utilization or unreasonable consumption of battery. us, the energy consumption of mobile terminal is still a focus for many researchers [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

A Tool for Energy Consumption Monitoring and Analysis of the Android Terminal

Cui

Bai

et al. 2021

Journal of Electrical and Computer Engineering

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With the rapid development of communication technology, the intelligent mobile terminal brings about great convenience to people’s life with rich applications, while its power consumption has become a great concern to researchers and consumers. Power modeling is the basis to understand and analyze the power consumption characteristics of the terminal. In this paper, we analyze the Bluetooth and hidden power consumption of the android platform and fix the power model of open-source Android platform. Then, a power consumption monitoring tool is implemented based on the model; the tool is divided into three layers, which are original information monitor layer, power consumption calculation layer, and application layer. The original monitor layer gets the power consumption data and running time of the different components under different states, the calculation layer calculates the power consumption of each hardware and each application based on the power model of each component, and the application layer displays the real-time power consumption of the software and hardware. Finally, we test our tool in real environment by using Xiaomi 9 Pro and perform comparison with actual instrument measurement; the error between the monitored value and the measured value is less than 5%.

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