Density-adaptive range-free localization in large-scale sensor networks

Location information is crucial for many applications in wireless sensor networks. While many types of localization algorithms have been proposed in the literature, the limitations on the cost and hardware of sensors have made range-free localization schemes more practical than the others. However, the previous range-free schemes have seldom considered the impact of the local node density on the single hop range (SHR) estimation. In this paper, using the local node density we redefine the SHR. On top of the new SHR, we propose a novel correction scheme, namely SHR correction scheme (SCS), for multi-hop range-free distance estimation and localization. Compared with the other range-free distance estimation and localization methods, SCS reduces the range estimation and localization error significantly, even when the number of anchors is low.