EMGODV-Hop: an efficient range-free-based WSN node localization using an enhanced mountain gazelle optimizer

Accurate node localization is essential in wireless sensor networks (WSNs) for effective data analysis and the successful operation of applications like environmental monitoring and disaster management. Range-free methods like the distance vector-hop (DV-hop) algorithm are often used due to hardware and cost constraints, but they face challenges in accuracy and stability. The NP-hard nature of the localization problem has led to the integration of metaheuristic algorithms in previous studies to enhance performance. This paper presents EMGODV-Hop, a novel approach for node localization in multi-hop networks that combines the DV-Hop algorithm with the mountain gazelle optimization (MGO) algorithm to enhance localization precision. The EMGODV-Hop method operates in two phases: First, it uses an improved variant of the DV-Hop algorithm to more accurately estimate distances between unknown and anchor nodes by incorporating a correction factor. Next, it employs an enhanced version of MGO algorithm, referred to as EMGO, to determine the positions of WSN nodes. The improved DV-Hop version enhances accuracy by incorporating a correction factor for better estimation of hop distances, while the EMGO algorithm addresses the limitations of the original MGO algorithm and improves its search capabilities. Extensive simulations assessed the effectiveness of the proposed method across various factors, including anchor node ratios, total node count, and communication ranges. The results demonstrate significant accuracy improvements with the proposed algorithm, showing enhancements of 48.69%, 26.22%, 19.33%, 28.21%, and 40.47% compared to DV-Hop, MGODV-Hop, PSODV-Hop, WSODV-Hop, and SSADV-Hop, respectively.