An Empirical Analysis of Mobile Energy Consumption Across User Configurations

TL;DR

This study systematically quantifies how user-controlled device and app settings affect energy consumption on mobile devices, providing practical insights for optimizing battery life.

Contribution

It introduces an automated framework to measure the energy impact of user settings across popular apps, bridging technical analysis and end-user practical guidance.

Findings

Screen brightness and refresh rate significantly affect energy use.

Lowering video resolution reduces app energy consumption.

Battery-saving profiles can extend device autonomy by up to 20%.

Abstract

Mobile devices have become ubiquitous tools for communication, entertainment, and productivity, yet battery autonomy remains a constraint. While energy-saving tips exist, they are often generic, anecdotal, or focused on software development rather than end-user behavior, leaving users to rely on grey literature or tacit knowledge to optimize their device energy consumption, lacking the academic rigor to ensure their effectiveness. This research aims to bridge the gap between technical energy analysis and practical user application by quantifying the energy consumption of different user-controlled parameters. Employing an automated monitoring framework, a series of user interface tests that simulate realistic usage patterns across popular applications (i.e., WhatsApp, Instagram, TikTok, and YouTube) was conducted. The objective is to have a systematic evaluation of the energy impact of user-controllable factors, including device settings, such as screen brightness, refresh rate, connectivity status, interface themes, and battery-saving profiles, combined with more app-specific variables (e.g., video resolution and message size). By analyzing over 12,000 data points, this paper quantifies the real-world impact of common settings, revealing the trade-offs between user experience and device autonomy.