Wireless Sensor Network Localization Incorporating Gray Wolf Optimization and DV-Hop Algorithm

Abstract

The rapid advancement of wireless sensor networks has made network node localization technology a crucial area of study. However, the current network node localization methods have low accuracy. To address this situation, the study introduces the concepts of hopping distance error and automatic adjustment of communication radius on the basis of the traditional DV-Hop algorithm. Weighting coefficients are introduced to assign weights to the hopping distance error, thus realizing the hopping distance correction. The planning of hopping distance between nodes is also realized by the method of multi-communication radius adjustment. Then the research uses the gray wolf algorithm to optimize the matrix operation method in the positioning algorithm. On the basis of the traditional gray wolf algorithm, the research also uses the idea of the particle swarm algorithm to improve its updating method. The results indicated that the research-designed model showed more satisfactory localization effects in different scenarios. Specifically, the average localization error of the research-designed model was kept below 0.18m, and its average running time was 0.787s. Comprehensively, the research-designed model is able to have better performance in wireless sensor network node localization, which can provide new technical support for the field of wireless networks.

Keywords

• Wireless sensor network
• DV-Hop
• localization
• gray wolf algorithm
• weighting coefficients
• communication radius