Localization in Wireless Sensor Networks Based Enhanced Horned Lizard Optimization Algorithm

In wireless sensor networks (WSNs), numerous sensor nodes collect environmental data, but this data becomes meaningless without accurate locations. Therefore, in many WSN applications, including industrial, whether, military, and health, sensor node localization is crucial. It seeks to identify unknown node positions based on anchor node positions. Since traditional localization schemes, such as GPS, are not appropriate for WSN implementation because of high cost and low indoor performance, the researchers are creating alternative localization schemes. In this work, we present a nodes localization issue in WSNs based on the Enhanced Horned Lizard Optimization Algorithm (EHLOA). A comparison analysis is conducted with the standard HLOA scheme to assess the proposed EHLOA. The proposed EHLOA performs better than the standard HLOA technique by achieving faster convergence and reducing average localization error (ALE) and mean localization error (MLE).