A Method for Characterizing Energy Consumption in Android Smartphones Authors: Luis Corral, Anton B. Georgiev, Alberto Sillitti, Giancarlo Succi Center for Applied Software Engineering, Free University of Bozen/Bolzano, Bolzano, Italy GREENS 2013, ICSE 2013 San Francisco, CA, USA 20.05,2013

Motivation  Smartphones have a market penetration in millions both in active users and sold devices.  Power autonomy requirements of mobile devices with rapidly increasing computing capabilities.  Reduce battery garbage.  In order to save energy first we need to measure it. L. Corral, A. Georgiev, A. Sillitti, G. Succi | Center for Applied Software Engineering | Free University of Bozen/Bolzano

Our approach  We aim to characterize the energy consumption based on the time that battery lasts.  relate the status of the components of the smartphone with the battery level  collect available sensors' data surveying parameters exposed by OS  CharM - Android application tool for collecting energy related OS parameters of the device component.  Experiment:  Setup - Three devices with different hardware and software configurations ( HTC Nexus One, Samsung Galaxy, Nexus 7 tablet,)  Data Collection – Three stages with multiple 2 hours long iterations:  Normal Mode – daily usage of the device, serve as a baseline.  Airplane Mode – all the communication interfaces disabled.  Component stress Mode – every iteration one of the components was put in high power consumption state, while the others were disabled. L. Corral, A. Georgiev, A. Sillitti, G. Succi | Center for Applied Software Engineering | Free University of Bozen/Bolzano

Results L. Corral, A. Georgiev, A. Sillitti, G. Succi | Center for Applied Software Engineering | Free University of Bozen/Bolzano Execution ModeNexus One Nexus 7Galaxy Nexus Normal mode10%2%4% Airplane mode2%0.2%1% CPU stress40%17%26% OLED stress35%24%20% Video playback stress 12%7%10% WiFi stress24%22%32% GPS stress17%10%15% Percentage of Battery Discharge in 2 Hours ComponentImpact to discharge cycle (average) 1. CPU stress27.66% 2. OLED stress26.33% 3. WiFi interface26.00% 4. GPS interface14.00% 5. Video playback9.60% 6. Normal mode5.33% 7. Airplane mode1.06%  500+ hours of data collection.  The most energy hungry components are CPU, OLED and WIFI interface. Ranking of Energy Hungry Components

Challenges  Improve CharM:  Add more parameters that can be taken from the OS (e.g. battery temperature).  Provide enhanced reporting features (e.g. customized plots, tables and reports).  Improve collected data accuracy and completeness.  Green metrics?  Green security?  Testing for energy efficiency? L. Corral, A. Georgiev, A. Sillitti, G. Succi | Center for Applied Software Engineering | Free University of Bozen/Bolzano

Questions? L. Corral, A. Georgiev, A. Sillitti, G. Succi | Center for Applied Software Engineering | Free University of Bozen/Bolzano