Abstract
Wireless-sensor networks (WSNs) are networks of autonomous nodes used for monitoring an environment. Developers of WSNs face challenges that arise from communication link failures, memory and computational constraints, and limited energy. Many issues in WSNs are formulated as multidimensional optimization problems and approached through bioinspired techniques. Particle swarm optimization (PSO) is a simple, effective, and computationally efficient optimization algorithm. It has been applied to address WSN issues such as optimal deployment, node localization, clustering, and data aggregation. This paper outlines issues in WSNs, introduces PSO, and discusses its suitability for WSN applications. It also presents a brief survey of how PSO is tailored to address these issues. © 2011 IEEE.
Recommended Citation
R. V. Kulkarni and G. K. Venayagamoorthy, "Particle Swarm Optimization in Wireless-sensor Networks: A Brief Survey," IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, vol. 41, no. 2, pp. 262 - 267, article no. 5518452, Institute of Electrical and Electronics Engineers, Mar 2011.
The definitive version is available at https://doi.org/10.1109/TSMCC.2010.2054080
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Clustering; data aggregation; localization; optimal deployment; particle swarm optimization (PSO); Wireless-sensor networks (WSNs)
International Standard Serial Number (ISSN)
1094-6977
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Mar 2011
Comments
National Science Foundation, Grant ECCE # 0348221