Distributed Estimation of Anomalies using a Low Complexity PSO Algorithm

Any wireless sensor network can experience anomalies that can hinder performance. This work presents a distributed estimation algorithm that estimates any such anomalies using a PSO algorithm. PSO algorithms are computationally expensive. This work presents a low complexity version of the algorithm...

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Bibliographic Details
Published in2024 International Conference on Emerging Trends in Smart Technologies (ICETST) pp. 1 - 4
Main Authors Saeed, Muhammad Omer Bin, Khan, Salman A., Butt, Naveed R., Mohammad, Nazeeruddin, Zerguine, Azzedine
Format Conference Proceeding
LanguageEnglish
Published IEEE 10.10.2024
Subjects
Computational complexity
Computational efficiency
Convergence
Distributed Estimation
Estimation
Event Triggering
Filtering algorithms
Low Complexity
Particle swarm optimization
Self-Organizing Hierarchical PSO
Wireless communication
Wireless sensor networks
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Summary:Any wireless sensor network can experience anomalies that can hinder performance. This work presents a distributed estimation algorithm that estimates any such anomalies using a PSO algorithm. PSO algorithms are computationally expensive. This work presents a low complexity version of the algorithm that removes redundant computations and achieves excellent performance as well. Low complexity algorithms are essential for a longer battery life of wireless sensor so this algorithm provides an excellent alternative to the basic linear adaptive filtering algorithms that have low complexity but require a lot more time to achieve similar results.
DOI:10.1109/ICETST62952.2024.10737959