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

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 t...

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Published inCircuits, 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
LanguageEnglish
Published New York Springer US 01.03.2025
Springer Nature B.V
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ISSN0278-081X
1531-5878
DOI10.1007/s00034-024-02910-z

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Abstract 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.
AbstractList 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.
Author Mohammad, Nazeeruddin
Bin Saeed, Muhammad Omer
Khan, Salman A.
Butt, Naveed R.
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Distributed estimation
Low complexity
Event triggering
Particle swarm optimization
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Snippet This work explores the possibility of reducing computations in a distributed estimation setup, utilizing a self organizing hierarchical particle swarm...
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SubjectTerms 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
Title A Time-Critical Low Complexity Distributed Self Organizing Hierarchical Particle Swarm Optimization Algorithm for Wireless Sensor Networks
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