Energy-Efficient Position Tracking in Proactive Location-Based Services for Smartphone Environments

Location-based services (LBSs) gain a massive shift in popularity these days and are about to take the next step towards proactive LBSs. In comparison to conventional LBSs, their proactive variant needs continuous position tracking to monitor spatial objects to detect the relationships between a user and surrounding objects and proactively perform actions. But tracking so far also results in severe battery drain in mobile devices due to deficient positioning APIs and the absence of energy-efficient positioning methods with adequate accuracy. By exploiting the combined information from several positioning technologies with different characteristics in terms of energy consumption, accuracy, precision and availability, this paper proposes a hierarchical positioning algorithm, which provides a general algorithmic optimization in order to extend existing positioning APIs to energy-efficiently track a user´s position without diminishing accuracy. The algorithm dynamically deactivates different positioning technologies and only activates the positioning method with the least energy consumption that at the same time provides sufficient accuracy to correctly determine topological relationships. In that way, the algorithm can reliably and accurately determine, if the user leaves or enters predefined geographic areas to trigger events for proactive LBSs while preserving valuable energy resources. First results on Android handsets show a reduction in energy consumption of up to 90 percent in comparison to conventional GPS tracking.