3D many-objective DV-hop localization model with NSGA3

Abstract

Wireless sensor location is a challenging task issue in the Internet of Things (IoT). Distance vector-hop (DV-hop) algorithm provides a range-free positioning scheme, but its position prediction method based on least square method brings a large positioning error. To overcome this issue, this paper constructs a three-dimensional (3D) many-objective positioning model. Specifically, we consider many factors, such as the error characteristics of the estimated distance, the distribution characteristics of nodes and the computational cost. Based on these factors, we propose a many-objective 3D-DV-hop positioning model, and propose a data preprocessing strategy and outlier removal strategy. Finally, a fashionable many-objective optimization algorithm is employed to solve the model. The experimental results show that the model proposed in this paper has great advantages in accuracy and robustness, and is superior to the current single and multi-objective positioning model.