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<p>The rapid advancement of Wireless Sensor Networks (WSN) has led to the development of a wide variety of localization techniques. This enables various tasks, such as environmental, health, and crop monitoring, etc. Researchers have proposed numerous approaches ranging from classical range-based and range-free methods to more recent machine learning and optimization-driven solutions. These contributions are often presented in isolation, making it difficult to obtain a unified understanding of their relative strengths and limitations. Therefore, there is a need of a comprehensive survey that systematically organizes existing localization techniques into a coherent framework. The paper presents an extensive survey of range-free, range-based, machine-learning-based, and metaheuristics-based techniques. Further, the surveyed methods are systematically classified based on mathematical models, accuracy, sensitivity, measurement models, anchor utilization, energy efficiency, and scalability, etc. This survey aims to provide a comprehensive understanding of localization techniques and future research directions in node localization in WSNs.</p>

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From Classical to Intelligent Methods: A Comprehensive Survey of Node Localization Algorithms and Techniques in Wireless Sensor Networks

  • 期刊论文

  • 发表日期：

    2026年4月23日

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  • Akash Raghuvanshi,
  • Vartika Puri,
  • Awadhesh Kumar

摘要

The rapid advancement of Wireless Sensor Networks (WSN) has led to the development of a wide variety of localization techniques. This enables various tasks, such as environmental, health, and crop monitoring, etc. Researchers have proposed numerous approaches ranging from classical range-based and range-free methods to more recent machine learning and optimization-driven solutions. These contributions are often presented in isolation, making it difficult to obtain a unified understanding of their relative strengths and limitations. Therefore, there is a need of a comprehensive survey that systematically organizes existing localization techniques into a coherent framework. The paper presents an extensive survey of range-free, range-based, machine-learning-based, and metaheuristics-based techniques. Further, the surveyed methods are systematically classified based on mathematical models, accuracy, sensitivity, measurement models, anchor utilization, energy efficiency, and scalability, etc. This survey aims to provide a comprehensive understanding of localization techniques and future research directions in node localization in WSNs.