Sanae Rosen
ABSTRACT
Energy consumption due to network traffic on mobile devices continues to be a significant concern. We examine a range of excessive energy consumption problems caused by background network traffic through a two-year user study, and also validate these findings through in-lab testing of the most recent versions of major mobile apps. We discover a new energy consumption problem where foreground network traffic persists after switching from the foreground to the background, leading to unnecessary energy and data drain. Furthermore, while we find some apps have taken steps to improve the energy impact of periodic background traffic, energy consumption differences of up to an order of magnitude exist between apps with near-identical functionality. Finally, by examining how apps are used in the wild, we find that some apps continue to generate unneeded traffic for days when the app is not being used, and in some cases this wasted traffic is responsible for a majority of the app's network energy overhead. We propose that these persistent, widespread and varied sources of excessive energy consumption in popular apps should be addressed through new app management tools that tailor network activity to user interaction patterns.
- App Programming Guide for iOS -- Background Execution. https://developer.apple.com/library/prerelease/ios/documentation/iPhone/Conceptual/iPhoneOSProgrammingGuide/BackgroundExecution/BackgroundExecution.html.Google Scholar
- Apple's app store has passed 100 billion app downloads. http://www.theverge.com/2015/6/8/8739611/apple-wwdc-2015-stats-update.Google Scholar
- Background agents for Windows Phone 8. https://msdn.microsoft.com/en-us/library/windows/apps/Hh202942(v=VS.105).aspx.Google Scholar
- Conserve windows phone battery life by managing background apps. http://www.windowscentral.com/conserve-windows-phone-battery-life- managing-background-apps.Google Scholar
- Developer preview - power-saving optimizations. https://developer.android.com/preview/features/power-mgmt.html.Google Scholar
- ActivityManager.RunningAppProcessInfo documentation. https://developer.android.com/reference/android/app/ActivityManager.RunningAppProcessInfo.html.Google Scholar
- P. K. Athivarapu, R. Bhagwan, S. Guha, V. Navda, R. Ramjee, D. Arora, V. N. Padmanabhan, and G. Varghese. RadioJockey: Mining Program Execution to Optimize Cellular Radio Usage. In Proc. ACM MobiCom, 2012. Google ScholarDigital Library
- A. Aucinas, N. Vallina-Rodriguez, Y. Grunenberger, V. Erramilli, K. Papagiannaki, J. Crowcroft, and D. Wetherall. Staying Online while Mobile: The Hidden Costs. In CoNEXT, 2013. Google ScholarDigital Library
- N. Balasubramanian, A. Balasubramanian, and A. Venkataramani. Energy Consumption in Mobile Phones: A Measurement Study and Implications for Network Applications. In Proc. ACM IMC, 2009. Google ScholarDigital Library
- X. Chen, N. Ding, A. Jindal, Y. C. Hu, M. Gupta, and R. Vannithamby. Smartphone energy drain in the wild: Analysis and implications. In Proc. Sigmetrics, 2015. Google ScholarDigital Library
- E. Cuervo, A. Balasubramanian, D. ki Cho, A. Wolman, S. Saroiu, R. Chandra, and P. Bahl. MAUI: Making Smartphones Last Longer with Code Offload. In Proc. ACM MobiSys, 2010. Google ScholarDigital Library
- H. Falaki, D. Lymberopoulos, R. Mahajan, S. Kandula, and D. Estrin. A First Look at Traffic on Smartphones. In Proc. ACM IMC, 2010. Google ScholarDigital Library
- H. Falaki, R. Mahajan, S. Kandula, D. Lymberopoulos, R. Govindan, and D. Estrin. Diversity in Smartphone Usage. In Proc. ACM MobiSys, 2010. Google ScholarDigital Library
- A. Gember, A. Akella, J. Pang, A. Varshavsky, and R. Caceres. Obtaining In-Context Measurements of Cellular Network Performance. In Proc. ACM IMC, 2012. Google ScholarDigital Library
- R. Holly. Checking out Doze and App standby on the Android M Developer Preview. http://www.androidcentral.com/checking-out-doze-android-m-developer-preview.Google Scholar
- J. Huang, F. Qian, A. Gerber, Z. M. Mao, S. Sen, and O. Spatscheck. A Close Examination of Performance and Power Characteristics of 4G LTE Networks. In Proc. ACM MobiSys, 2012. Google ScholarDigital Library
- J. Huang, F. Qian, Y. Guo, Y. Zhou, Q. Xu, Z. M. Mao, S. Sen, and O. Spatscheck. An In-Depth Study of LTE: Effect of Network Protocol and Application Behavior on Performance. In ACM SIGCOMM Computer Communication Review, volume 43, 2013. Google ScholarDigital Library
- J. Huang, F. Qian, Z. M. Mao, S. Sen, and O. Spatscheck. Screen-off Traffic Characterization and Optimization in 3G/4G Networks. In Proc. ACM IMC, 2012. Google ScholarDigital Library
- J. Huang, Q. Xu, B. Tiwana, Z. M. Mao, M. Zhang, and P. Bahl. Anatomizing Application Performance Differences on Smartphones. In Proc. ACM MobiSys, 2010. Google ScholarDigital Library
- M. Martins, J. Cappos, and R. Fonseca. Selectively Taming Background Android Apps to Improve Battery Lifetime. In Proc. Usenix ATC, 2015. Google ScholarDigital Library
- F. Qian, Z. Wang, Y. Gao, J. Huang, A. Gerber, Z. Mao, S. Sen, and O. Spatscheck. Periodic Transfers in Mobile Applications: Network-wide Origin, Impact, and Optimization. In Proceedings of the 21st international conference on World Wide Web, pages 51--60, 2012. Google ScholarDigital Library
- F. Qian, Z. Wang, A. Gerber, Z. M. Mao, S. Sen, and O. Spatscheck. Profiling Resource Usage for Mobile Applications: a Cross-layer Approach. In Proc. ACM MobiSys, 2011. Google ScholarDigital Library
- A. A. Sani, Z. Tan, P. Washington, M. Chen, S. Agarwal, L. Zhong, and M. Zhang. The Wireless Data Drain of Users, Apps, & Platforms. ACM SIGMOBILE Mobile Computing and Communications Review, 17(4), 2013. Google ScholarDigital Library
- I. Singh, S. V. Krishnamurthy, H. V. Madhyastha, and I. Neamtiu. ZapDroid: Managing Infrequently Used Applications on Smartphones. In Proc. UbiComp, 2015. Google ScholarDigital Library
- J. Sommers and P. Barford. Cell vs. WiFi: On the Performance of Metro Area Mobile Connections. In Proc. ACM IMC, 2012. Google ScholarDigital Library
- N. Thiagarajan, G. Aggarwal, A. Nicoara, D. Boneh, and J. P. Singh. Who Killed my Battery?: Analyzing Mobile Browser Energy Consumption. In Proceedings of the 21st international conference on World Wide Web, 2012. Google ScholarDigital Library
- Q. Xu, J. Erman, A. Gerber, Z. Mao, J. Pang, and S. Venkataraman. Identifying Diverse Usage Behaviors of Smartphone Apps. In Proc. ACM IMC, 2011. Google ScholarDigital Library
Index Terms
- Revisiting Network Energy Efficiency of Mobile Apps: Performance in the Wild
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