Heterogeneous cooperative localization for social networks with mobile devices

Location-aware techniques, which combine multiple sensors in the smart-phone, have been researched and developed to estimate accurate locations of the mobile users in the social networks. In cooperative localization, each mobile user with the WiFi and GPS sensors works in a peer-to-peer, independent and assistant mode. This paper provides a comparison of four probabilistic cooperative localization algorithms for smart-phone applications: Centroid method, Nearest Neighbor method, Kernel method and AP density method. The location of the unknown mobile user is estimated based on Receive Signal Strength (RSS) from the shared APs and GPS locations from reference nodes. An empirical evaluation of the system is given to demonstrate the feasibility of these algorithms by reporting the results in a real-world environment. And a Monte Carlo simulation is also carried out to evaluate the performance of the cooperative algorithms for social networks.