A Time-Critical Low Complexity Distributed Self Organizing Hierarchical Particle Swarm Optimization Algorithm for Wireless Sensor Networks

• Published in: Circuits, systems, and signal processing Vol. 44; no. 3; pp. 2180 - 2195
• Main Authors: Bin Saeed, Muhammad Omer, Khan, Salman A., Butt, Naveed R., Mohammad, Nazeeruddin
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2025; Springer Nature B.V
• Subjects: Algorithms; Circuits and Systems; Computer engineering; Cooperation; Cybersecurity; Electrical Engineering; Electronics and Microelectronics; Engineering; Instrumentation; Internet of Things; Optimization algorithms; Particle swarm optimization; Science; Sensors; Short Paper; Signal processing; Signal,Image and Speech Processing; Wireless sensor networks; Self organizing hierarchical PSO; Distributed estimation; Low complexity; Event triggering; Particle swarm optimization
• ISSN: 0278-081X; 1531-5878
• DOI: 10.1007/s00034-024-02910-z

This work explores the possibility of reducing computations in a distributed estimation setup, utilizing a self organizing hierarchical particle swarm optimization algorithm. Reducing computations is essential for any application using wireless sensors in a distributed network, as the sensors need to save processing power in order to last longer. An event triggering approach is used to remove redundant computations from the algorithm. This results in a slight degradation in performance but the trade-off is a significant reduction in computations. In practical applications, such as intruder detection in a cybersecurity setup, the proposed algorithm can prove to be an asset with its rapid estimation compared with the standard algorithms.