Cooperative Positioning and Tracking in Disruption Tolerant Networks

With the increasing number of location-dependent applications, positioning and tracking a mobile device becomes more and more important to enable pervasive and context-aware service. While extensive research has been performed in physical localization and logical localization for satellite, GSM and WiFi communication networks where fixed reference points are densely-deployed, positioning and tracking techniques in a sparse disruption tolerant network (DTN) have not been well addressed. In this paper, we propose a decentralized cooperative method called PulseCounting for DTN localization and a probabilistic tracking method called ProbTracking to confront this challenge. PulseCounting evaluates the user walking steps and movement orientations using accelerometer and electronic compass equipped in cellphones. It estimates user location by accumulating the walking segments, and improves the estimation accuracy by exploiting the encounters of mobile nodes. Several methods to refine the location estimation are discussed, which include the adjustment of trajectory based on reference points and the mutual refinement of location estimation for encountering nodes based on maximum-likelihood. To track user movement, the proposed ProbTracking method uses Markov chain to describe movement patterns and determines the most possible user walking trajectories without full record of user locations. We implemented the positioning and tracking system in Android phones and deployed a testbed in the campus of Nanjing University. Extensive experiments are conducted to evaluate the effectiveness and accuracy of the proposed methods, which show an average deviation of 9m in our system compared to GPS.