A Mobile Beacon-assisted Node Localization Algorithm Using Network-Density-based Clustering for Wireless Sensor Networks
Zhao Fang①; Ma Yan①; Luo Hai-yong②; Lin Quan③; Lin Lin①
①School of Software Engineering, Researching Acadamy of Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China; ②Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China; ③School of Software Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
Abstract：All the current mobile beacon-assisted localization algorithms do not make full use of the practical node distribution information and let the mobile landmark travel the entire network, which causes large path length and low beacon utilization ratio. A novel mobile beacon-assisted node localization algorithm using network-density-based clustering (MBL(ndc)) for wireless sensor networks is presented, which combines node clustering, incremental localization and mobile beacon assisting together. It first selects the cluster heads that has highest core density, and then employs density-reachable method to cluster the network into several branches with the same density, and lastly obtains the optimum trajectory of mobile beacon by combining cluster head path planning using genetic algorithm with in-cluster path planning using hexagon trajectory. After the cluster heads and nearby nodes have completed localization, they become beacons, then cooperate with each other to localize the left unknown nodes in an incremental way. 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.
2009, Vol. 31 
