MultiMulti-objective 3objective 3objective 3objective 3-Dimensional DV-Hop Localization Algorithm with NSGA-II

Location information is generally considered to be indispensable information in wireless sensor networks, but existing algorithms have notable limitations in their positioning accuracy in 3-dimensional (3D) spaces. To improve the positioning accuracy of nodes in a 3D scenario, this paper proposes a new method called N2-3DDV-Hop (non-dominated sorting genetic algorithm II with 3D distance-vector hop) that builds on the 3D-DV-Hop algorithm by adding multi-objective model and NSGA-II. In this paper, it is analyzed that the limitations of the traditional single-objective positioning model and showed the relationship among the average hop distance, the number of sensor nodes, and the theoretical average distance. In addition then, the multi-objective positioning model incorporating the NSGA-II algorithm is presented. To evaluate its performance relative to other current methods, we compared our method by testing all of the methods with three different complex network topologies. Simulation results demonstrate that the N2-3DDV-Hop offered the best overall positioning performance compared with other algorithms and better robustness than the 3DDV-Hop algorithm.