Application power consumption estimation considering software dependency in Android

Kurihara, Shun; Fukuda, Shinji; Hamanaka, Shintaro; Oguchi, Masato; Yamaguchi, Saneyasu

doi:10.1145/3022227.3022312

Cited by 5 publications

(9 citation statements)

References 7 publications

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“…A method for improving the accuracy of monitoring the time of GPS usage was presented in the work of Ref. [4].…”

Section: Related Workmentioning

confidence: 99%

“…We consider the software dependency with examples of GPS and WakeLock in this paper. It is mainly because these usages are important for discussing power consumption [4], [7]. This paper is an extended version of the previously published work of Refs.…”

Section: Introductionmentioning

confidence: 99%

“…In order to reduce battery consumption by uninstalling a non-important application, understanding the power consumption of each application is required. However, the sizes of the increased and decreased power consumption by installing and uninstalling an application depends on the device [4], [5]. As far as we know, there is no method for obtaining this information.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, in order to accurately estimate the power consumption of each application, it is essential to improve the accuracy of the monitoring and estimating times considering the dependency. We propose a method for estimating the power consumption with consideration of software dependency [4], [5] only for applications which use GPS. The method was effective for applications using GPS.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Power Consumption of Each Application Considering Software Dependency in Android

Kurihara

Fukuda

Kamiyama

et al. 2019

Journal of Information Processing

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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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“…A method for improving the accuracy of monitoring the time of GPS usage was presented in the work of Ref. [4].…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of Power Consumption of Each Application Considering Software Dependency in Android

Kurihara

Fukuda

Kamiyama

et al. 2019

Journal of Information Processing

Self Cite

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show abstract

“…In our previous works, we proposed methods for estimating power consumption of each application [23], [24], [25] and methods for accelerating the speeds of tests and monitoring application behaviors [26], [27], [28], [29]. These works presented the detailed discussion on power consumption and its estimation on smartphones.…”

Section: Related Workmentioning

confidence: 99%

BET Estimation on Power Saving by Intermittent Disabling Network Interface on Android

Murakami

Kamiyama

Fukuda

et al. 2019

Journal of Information Processing

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The large power consumption of smartphones is an important issue. Smartphone operating systems such as Android have a function that invokes an application without user's operation. That is, an application runs and may communicate using its network interface in the screen-off state without user's operation. This behavior consumes large batteries. Temporarily disabling its network interface is one of the promising methods for reducing power consumption in the screen-off state. Less power is consumed while its network interface is disabled, but processes of disabling and enabling its network interface consume battery. Therefore, it is necessary to keep the interface disabled for a sufficiently long period such that the power consumption decreased by disabling the network interface exceeds the power consumption increased by the transition process of disabling and enabling the interface. In this paper, we focus on a method of reducing power consumption in the screen-off state by repeating to disable and enable the network interface and discuss estimation of its Break-Even Time (BET) with which the sizes of increased and decreased power consumption are the same. We then propose two methods for estimating BET. One method estimates BET by integrating the electric current. The other method estimates it according to the average electric current. We evaluate the methods with practical applications and Android devices and show that the method based on the average electric current can estimate BET accurately. In the case of our experiments, the difference between the actual and estimated BETs was less than 16.4%.

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Estimation of Power Consumption of Each Application Caused by Device Lock Considering Software Dependency in Smartphones

Kurihara

Fukuda

Oguchi

et al. 2017

2017 Fifth International Symposium on Computing and Networking (CANDAR)

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Application power consumption estimation considering software dependency in Android

Cited by 5 publications

References 7 publications

Estimation of Power Consumption of Each Application Considering Software Dependency in Android

Estimation of Power Consumption of Each Application Considering Software Dependency in Android

BET Estimation on Power Saving by Intermittent Disabling Network Interface on Android

Estimation of Power Consumption of Each Application Caused by Device Lock Considering Software Dependency in Smartphones

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