Power-saving localization techniques for mobile devices: A comparison between iOS and Android

This paper aims to develop generic strategies for improving energy consumption for location sensing on smartphones and compares the results of iOS and Android implementations. Mobile smartphone applications utilizing localization sensors (e.g. Global Positioning System) collectively face the problem of battery draining. Energy consumption is at a peak when applications permanently and stolidly use those sensors, even if their excessive exploitation is avoidable (e.g. when the user carrying the device is not moving).

Considering contextual parameters affecting localization of mobile devices (i.e. incorporating movement probability, speed, etc.) is the basic idea for developing a strategy capable of reducing energy consumption for location determination on mobile devices. This paper explains the paradigm and draws the architecture for a generic context-based energy saving strategy for mobile location-based services.

The paper reveals the positive implications in terms of energy consumption measured in the course of exhaustive tests for iOS and Android devices and discusses accuracy issues and potential workarounds, especially focusing on Apple’s M7 motion co-processor for consuming accelerometer data on a low energy level.

The paper identifies and measures energy issues for location determination on smartphones and presents a generic and heuristic concept for saving energy.