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An exploratory study on assessing the energy impact of logging on Android applications

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Abstract

Execution logs are debug statements that developers insert into their code. Execution logs are used widely to monitor and diagnose the health of software applications. However, logging comes with costs, as it uses computing resources and can have an impact on an application’s performance. Compared with desktop applications, one additional critical computing resource for mobile applications is battery power. Mobile application developers want to deploy energy efficient applications to end users while still maintaining the ability to monitor. Unfortunately, there is no previous work that study the energy impact of logging within mobile applications. This exploratory study investigates the energy cost of logging in Android applications using GreenMiner, an automated energy test-bed for mobile applications. Around 1000 versions from 24 Android applications (e.g., Calculator, FeedEx, Firefox, and VLC) were tested with logging enabled and disabled. To further investigate the energy impacting factors for logging, controlled experiments on a synthetic application were performed. Each test was conducted multiple times to ensure rigorous measurement. Our study found that although there is little to no energy impact when logging is enabled for most versions of the studied applications, about 79% (19/24) of the studied applications have at least one version that exhibit medium to large effect sizes in energy consumption when enabling and disabling logging. To further assess the energy impact of logging, we have conducted a controlled experiment with a synthetic application. We found that the rate of logging and the number of disk flushes are significant factors of energy consumption attributable to logging. Finally, we have examined the relation between the generated OS level execution logs and mobile energy consumption. In addition to the common cross-application log events relevant to garbage collection and graphics systems, some mobile applications also have workload-specific log events that are highly correlated with energy consumption. The regression models built with common log events show mixed performance. Mobile application developers do not need to worry about conservative logging (e.g., logs generated at rates of ≤ 1 message per second), as they are not likely to impact energy consumption. Logging has a negligible effect on energy consumption for most of the mobile applications tested. Although logs have been used effectively to diagnose and debug functional problems, it is still an open problem on how to leverage software instrumentation to debug energy problems.

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Acknowledgments

Shaiful Chowdhury is grateful to the Alberta Innovates - Technology Futures (AITF) to support his PhD research. Both Abram Hindle and Zhen Ming (Jack) Jiang are supported by an NSERC Discovery Grant.

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Authors and Affiliations

  1. Department of Computing Science, University of Alberta, Edmonton, AB, Canada

    Shaiful Chowdhury & Abram Hindle

  2. Gideon Smart Home, London, UK

    Silvia Di Nardo

  3. Software Construction, AnaLytics and Evaluation (SCALE) Lab, York University, Toronto, ON, Canada

    Zhen Ming (Jack) Jiang

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  1. Shaiful Chowdhury
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  2. Silvia Di Nardo
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  3. Abram Hindle
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  4. Zhen Ming (Jack) Jiang
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Correspondence to Shaiful Chowdhury.

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Communicated by: Maurizio Morisio

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Chowdhury, S., Di Nardo, S., Hindle, A. et al. An exploratory study on assessing the energy impact of logging on Android applications. Empir Software Eng 23, 1422–1456 (2018). https://doi.org/10.1007/s10664-017-9545-x

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