Optimization Algorithms for Wireless Sensor Networks Node Localization: An Overview

Abstract

Wireless Sensor Networks (WSNs) play a critical role in numerous applications, and the accurate localization of sensor nodes is vital for their effective operation. In recent years, optimization algorithms have garnered significant attention as a means to enhance WSN node localization. This paper presents an in-depth exploration of the necessity of localization in WSN nodes and offers a comprehensive review of optimization algorithms used for this purpose. The review encompasses a diverse range of optimization techniques, including evolutionary algorithms, swarm intelligence, and metaheuristic approaches. Key factors, such as localization accuracy, scalability, computational complexity, and robustness, are systematically evaluated and compared across various optimization algorithms. Additionally, the paper sheds light on the strengths and limitations of each optimization approach and discusses their applicability in different WSN deployment scenarios. The insights provided in this review serve as a valuable resource for researchers and practitioners seeking to optimize WSN node localization, thus promoting the efficient and reliable operation of WSNs in diverse real-world applications.

Distance- and Angle-Based Hybrid Localization Integrated in the IEEE 802.15.4 TSCH Communication Protocol

“…There have been several studies on applying the IEEE 802.15.4 standard and related IoT technologies for localization, primarily using the RSSI metric for proximity-based and fingerprint-based localization methods [ 20 , 40 ]. Although the accuracy of RSSI-based localization systems is continuously improving with the development of ML algorithms [ 41 ], the main drawback remains. The high sensitivity of the RSSI metric to environmental changes [ 11 ] makes the localization system unreliable and case-specific to the particular scenario.…”