A Mobile Beacon-Assisted Localization Algorithm Based on Network-Density Clustering for Wireless Sensor Networks

Most existing mobile beacon-assisted localization algorithms do not make effective use of the node distribution information and let the mobile landmark traverse the entire network, which causes large path length and low utilization rate of beacon messages. In order to reduce the path length and use the mobile beacon more effectively, a novel mobile beacon-assisted localization algorithm based on network-density clustering (MBL(ndc)) for wireless sensor networks is presented, which combines node clustering, incremental localization and mobile beacon assisting together. Simulation results demonstrate that the proposed MBL(ndc) algorithm offers comparable localization accuracy as the mobile beacon-assisted localization algorithm with HILBERT trajectory, but with less than 50% path length of the later, which shortens the period of positioning the whole network.