Towards planet-scale localization on smartphones with a partial radiomap

Abstract

The majority of smartphone localization systems use Assisted-GPS for fine-grained localization in outdoor spaces or WiFi-based RSS (Received Signal Strength) technologies for coarse-grain positioning in indoor and outdoor spaces. The former consumes precious energy from mobile devices, is strictly affected by the environment (e.g., cloudy day, forests, etc.) and does not work in indoor spaces. The latter collects RSS from WiFi beams within a user's vicinity and transfers an RSS vector to the server for localization, in which the position of the user is disclosed possibly violating users' privacy. In this paper, we present BloomMap, an innovative and efficient algorithm that conducts a localization process without unveiling the user's location to the localization service, minimizing the energy consumption of the mobile unit and also minimizing the network traffic by not transferring large positioning structures to the client (i.e., known as radiomap). Our framework is designed for planet-scale RSS localization scenarios, which are expected to emerge in the near-future. In particular, a user may localize itself using a subset of a vast data repository of RSS signals that is updated in real time by smartphone wardrivers. Our preliminary evaluation shows that our propositions can localize a device without unveiling its location in approximately 80% less time, energy and network resources than competitive approaches. We also describe our WiFi-based prototype system developed on the Android OS. © 2012 ACM.