HFPSA: A Hybrid Fuzzy Logic, Particle Swarm Optimization and Simulated Annealing Mechanism for Sensor Node Localization

Wireless sensor networks have been adopted widely in various application and these networks play crucial role in numerous real-time monitoring systems. However, the event occurrence, detection of event and localizing the event are the crucial aspect of these networks. Accurate node localization in WSNs is essential for various applications, including environmental monitoring and military surveillance. However, conventional methods like trilateration frequently face challenges due to issues like signal attenuation and environmental obstacles, resulting in substantial localization errors in real-world settings. The main aim of this article is to overcome these challenges by developing and a hybrid localization approach that improves both accuracy and reliability in WSN node localization. The proposed approach uses a combination of particle swarm optimization with simulated annealing with RSSI based distance estimation mechanism. Moreover, this approach also uses Fuzzy logic model to handle the uncertainty in distance error measurement. The combination of these model is validated by measuring the performance by simulating the WSN localization environment where proposed HFPSA has reported improve localization performance by reducing the overall localization error.