Classic Clustering Algorithms in Wireless Sensor Networks

Clustering algorithms represent a fundamental approach in wireless sensor networks (WSNs). These algorithms partition sensor nodes into distinct clusters to optimize communication and collaboration efficiency. Typically leveraging node attributes or distance metrics for clustering, such algorithms implement mechanisms like cluster head selection, threshold-based grouping, or energy-aware partitioning. Key functions often include neighbor discovery protocols, cluster formation routines, and inter-cluster communication handlers. By organizing nodes into clusters, these algorithms significantly reduce network communication overhead while enhancing energy efficiency and reliability. Implementation commonly involves distributed computing paradigms where nodes autonomously execute clustering logic using localized information. Consequently, clustering algorithms serve as critical components in WSN architectures and remain widely adopted in both research and practical applications.