Three-dimensional DV-Hop based on improved adaptive differential evolution algorithm

Abstract

Wireless Sensor Networks have become an integral part of our lives with the advancement in the field of Internet of Technology. Multiple sensors operate together in Wireless Sensor Networks (WSNs) to collect data and communicate wirelessly with one another. For each sensor node’s data collection to be useful, it is essential to explore precise localization technology for WSNs. DV-Hop, as an easily implementable range-free localization algorithm, has gained significant popularity in the research community. As a result, many enhanced DV-Hop variations have been put out in the literature. However, the challenges of poor location accuracy associated with DV-Hop continue to spark interest among researchers, leading to further investigations and making it a preferred area for research in localization algorithms. Research in this paper proposes an improved version of three-dimensional DV-Hop algorithm based on improved adaptive differential evolution (3D-IADE DV-Hop). The proposed method optimizes the estimated coordinates using an improved version of adaptive differential evolution by controlling offspring generation behaviour. Moreover, we have demonstrated the superiority of 3D-IADE DV-Hop compared to other algorithms under consideration. The simulation results serve to strengthen our observations, confirming that the proposed algorithm outperforms its counterparts with enhanced performance and superiority.