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A Fuzzy Multiobjective Particle Swarm Optimized TS Fuzzy Logic Congestion Controller for Wireless Local Area Networks
Citation
Nyirenda, CN and Dawoud, DS and Dong, F and Negnevitsky, M and Hirota, K, A Fuzzy Multiobjective Particle Swarm Optimized TS Fuzzy Logic Congestion Controller for Wireless Local Area Networks, Journal of Advanced Computational Intelligence and Intelligent Informatics, 15, (1) pp. 41-54. ISSN 1343-0130 (2011) [Refereed Article]
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Copyright Statement
Copyright 2011 Fuji Technology Press Ltd.
Official URL: http://www.fujipress.jp/finder/xslt.php?mode=prese...
DOI: doi:10.20965/jaciii.2011.p0041
Abstract
A Takagi-Sugeno Fuzzy Logic Congestion Detection (TSFLCD) mechanism is proposed for IEEE 802.11 wireless Local Area Networks. A Fuzzy Preference based Multi-Objective Particle Swarm Optimization (FPMOPSO) mechanism, for tuning the input membership functions and the output scalars, is also proposed. An online adaptation mechanism that fine tunes the output scalars based on system dynamics is implemented. Compared to the Adaptive Random Early Detection (ARED) and the Mamdani inference based Fuzzy Logic Congestion Detection (FLCD) mechanisms, simulation resulsts show that the TSFLCD mechanism leads to more than 40% reduction in packet loss rate. It also leads to more than 25% and up to 14% reductions in jitter and delay respectively for real time traffic. This work lays a foundation for the development of simple multiobjective fuzzy congestion controllers in wireless LANs.
Item Details
Item Type: | Refereed Article |
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Keywords: | congestion, fuzzy logic, wireless LAN, particle swarm optimization |
Research Division: | Information and Computing Sciences |
Research Group: | Machine learning |
Research Field: | Neural networks |
Objective Division: | Information and Communication Services |
Objective Group: | Communication technologies, systems and services |
Objective Field: | Communication technologies, systems and services not elsewhere classified |
UTAS Author: | Negnevitsky, M (Professor Michael Negnevitsky) |
ID Code: | 75264 |
Year Published: | 2011 |
Deposited By: | Centre for Renewable Power Energy Systems |
Deposited On: | 2012-01-19 |
Last Modified: | 2018-03-18 |
Downloads: | 3 View Download Statistics |
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