A Multi-Objective Localization Algorithm with Real Average Distance in WSN

Location information is an essential requirement in wireless sensor networks (WSN), many wireless sensor applications would be limited without location information. Distance vector-hop (DV-Hop), as a typical path-dependence algorithm, utilizes the connectivity and multi-hop transmission for estimated positioning. However, a large positioning error is caused because of its simple and rough estimated method. In this work, we analyze the defects of the existing traditional single-objective and multi-objective model based on DV-Hop algorithm, and provide a multi-objective localization model based on the real average estimated distance of all beacon nodes. Then, we solve it using the multi-objective optimization algorithm (NSGA-II), and named it RAMGA-DV-Hop. Eventually, we tested it with different aspects, and the simulation results confirm our method significantly outperforms the DV-Hop and OCS-LC-DV-Hop. Moreover, compare with existing multi-objective localization algorithms, such as NSGAII-DV-Hop, its overall performance also has advantages.