The WSN Localization Algorithm Integrating Ranging Correction and Spider Wasp Optimization - YU Xiu-wu; XIAO Lin; LIU Yong; YE Lai (工程科学与技术)
ObjectiveIn the context of node localization in wireless sensor networks (WSNs), the non-range-based DV-Hop algorithm suffers from significant localization errors due to the inaccuracies in hop count estimation and the neglect of actual node distances. This paper proposes a modified DV-Hop algorithm that integrates distance correction and a Spider Wasp Optimization (SWO) algorithm to address these issues. The objective is to improve the accuracy of node localization and enhance the overall performance of the DV-Hop algorithm, making it more reliable in practical deployment scenarios.MethodsThe proposed algorithm consists of two main components: distance correction and optimization using Spider Wasp Optimization (SWO). First, the traditional hop count calculation is improved by adopting the Jaccard coefficient as the metric to increase the accuracy of hop count estimation. The Jaccard coefficient, a well-established similarity measure, ensures that the hop count reflects a more accurate estimate of the network's topology. After the hop count information is obtained, a credibility calculation is introduced to adjust the hop distances, allowing a more accurate representation of the actual distances between nodes.Results and Discussions　The proposed algorithm significantly outperforms the conventional DV-Hop algorithm and other related methods in terms of localization accuracy and energy efficiency. The use of the Jaccard coefficient for hop count estimation improves the precision of distance calculation, while the credibility adjustment further enhances the accuracy of node localization. The integration of SWO, with its improved population initialization and adaptive weighting mechanism, contributes to faster convergence and more precise localization results.ConclusionsThis study presents a novel hybrid localization algorithm that combines distance correction with Spider Wasp Optimization (SWO) for enhancing the DV-Hop algorithm. The integration of the Jaccard coefficient for hop count accuracy and the application of SWO with chaos mapping-based initialization, adaptive weighting, and Gaussian mutation significantly improves the localization precision and energy efficiency. The proposed algorithm demonstrates robustness against environmental changes and network dynamics, making it an effective solution for real-world wireless sensor network localization tasks. The results indicate that the algorithm offers a promising approach for improving the accuracy and reliability of node localization in large-scale WSNs.