An Enhanced DV-Hop Localization Algorithm Based on Variable Scene Applications in the IoT

The distance vector hop algorithm is commonly used for sensor node localization. However, its high localization accuracy error and stability issues make it unsuitable for many applications. To overcome these concerns, this article proposes a new function and binary distance vector hop (FBDV-Hop) algorithm with binary controllers and function correction methods while considering the application requirement. In FBDV-Hop, binary controllers are designed to analyze the optimization effect of the module fully and make it adaptable to diverse scenarios. The correction strategies were based on average hop distance measurement, estimated distance, equation composition method, and localization after supplementary correction, which were divided into four modules in accordance with the module error sources of different design correction functions. The simulation experiment was designed to analyze the principle of the role of each module in depth and achieve the optimal optimization effect. The experimental results show that the localization error optimization rate under the FBDV-Hop algorithm was more than 70%, and the optimization rate, stability, effectiveness, and adaptability of the algorithm were considerably greater than the baseline algorithms.