Node Position Computation Algorithms for Localization in Wireless Sensor Networks: A Systematic Literature Review
Abstract
Wireless Sensor Networks (WSNs) are widely applied in domains such as environmental monitoring, healthcare, and defense, where accurate localization of sensor nodes is essential for reliable data interpretation. Despite extensive research, localization continues to face challenges related to energy consumption, scalability, and algorithmic efficiency. This paper presents a systematic review of position computation algorithms, emphasizing how different approaches address these challenges. The analysis highlights key trade-offs, such as accuracy versus energy cost and convergence speed versus computational overhead. It also identifies clear research trends, including a shift from traditional range-based and range-free methods toward hybrid and AI-assisted techniques that enhance adaptability in dynamic environments. Persistent open issues remain, notably handling mobility, achieving robustness under noisy conditions, and enabling deployment in large-scale real-world settings. By synthesizing these insights, the study clarifies the current state of WSN localization, outlines unresolved gaps, and points to future directions for energy-aware, scalable, and learning-driven solutions.
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