Journal of Information Processing
Online ISSN : 1882-6652
ISSN-L : 1882-6652
Estimation of Power Consumption of Each Application Considering Software Dependency in Android
Shun KuriharaShoki FukudaTakeshi KamiyamaAkira FukudaMasato OguchiSaneyasu Yamaguchi
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2019 Volume 27 Pages 221-232

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Abstract

Some reports stated that the most important issue of smartphones is their large battery consumption. Information on the power consumption of each application is important for users and administrations of application distributing sites. Especially, information on power consumption of each application in the screen-off state is important because understanding the behavior of an application in the state is difficult. Naturally, the power consumption of a device increases and decreases by installing and uninstalling an application, respectively. However, the sizes of increase and decrease in power consumptions depend on the device. We think there are two types of dependencies, which are hardware and software dependencies. The hardware dependency is that the power consumption of an application depends on the hardware elements of the device. The software dependency is that the power consumption of an application depends on the other applications installed on the device. We then argue that consideration of these dependencies are essential for estimation of the power consumption of each application. In this paper, we focus on the software dependency and propose a method for estimating the size of increase and decrease in power consumptions of the device by installing and uninstalling an application considering software dependency. The proposed method monitors starts and ends of functions such as GPS usage and WakeLock, then estimates the parts of the power consumptions of each application separately. We estimate the GPS usage time and WakeLock time for evaluation of the proposed method and show that the proposed method can estimate these more accurately than the standard method of the Android operating system. Our evaluation demonstrated that the proposed method decreased the difference between the estimated and actual sizes of decreases in power consumption by 89% at most.

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© 2019 by the Information Processing Society of Japan
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