DV-Hop Algorithm Based on Multi-Objective Salp Swarm Algorithm Optimization

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 7; p. 3698
• Main Authors: Liu, Weimin, Li, Jinhang, Zheng, Aiyun, Zheng, Zhi, Jiang, Xinyu, Zhang, Shaoning
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 03.04.2023; MDPI
• Subjects: Accuracy; Algorithms; Analysis; Communication; Connectivity; DV-Hop; Energy consumption; Localization; Mathematical optimization; multi-objective salp swarm algorithm; node localization; Optimization; Sensors; wireless sensor network; Wireless sensor networks; node localization; multi-objective salp swarm algorithm; DV-Hop; wireless sensor network
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23073698

The localization of sensor nodes is an important problem in wireless sensor networks. The DV-Hop algorithm is a typical range-free algorithm, but the localization accuracy is not high. To further improve the localization accuracy, this paper designs a DV-Hop algorithm based on multi-objective salp swarm optimization. Firstly, hop counts in the DV-Hop algorithm are subdivided, and the average hop distance is corrected based on the minimum mean-square error criterion and weighting. Secondly, the traditional single-objective optimization model is transformed into a multi-objective optimization model. Then, in the third stage of DV-Hop, the improved multi-objective salp swarm algorithm is used to estimate the node coordinates. Finally, the proposed algorithm is compared with three improved DV-Hop algorithms in two topologies. Compared with DV-Hop, The localization errors of the proposed algorithm are reduced by 50.79% and 56.79% in the two topology environments with different communication radii. The localization errors of different node numbers are decreased by 38.27% and 56.79%. The maximum reductions in localization errors are 38.44% and 56.79% for different anchor node numbers. Based on different regions, the maximum reductions in localization errors are 56.75% and 56.79%. The simulation results show that the accuracy of the proposed algorithm is better than that of DV-Hop, GWO-DV-Hop, SSA-DV-Hop, and ISSA-DV-Hop algorithms.