Optimized DV-Hop Localization Algorithm Using PSO for IoT and WSNs

Abstract

Sensor node localization is a critical issue in various Internet of Things (IoT) and Wireless Sensor Network (WSN) applications that require precise location data. Among the proposed solutions, the DV-Hop algorithm has been widely adopted to address this issue. However, achieving high localization accuracy remains a significant research challenge. This study introduces a novel approach to minimizing errors in estimating the average hop size using a new formula. Furthermore, the metaheuristic particle swarm optimization (PSO) is integrated into the DV-Hop method to refine the estimated locations of sensor nodes, enhancing localization accuracy. Extensive simulations demonstrate that the proposed technique outperforms several existing methods. The results indicate that the proposed approach significantly improves localization accuracy, with the ODV-HopPSO algorithm surpassing existing methods in terms of error reduction.