A fuzzy multiobjective particle swarm optimized TS fuzzy logic congestion controller for wireless local area networks

Clement N. Nyirenda, Dawoud S. Dawoud, Fangyan Dong, Michael Negnevitsky, Kaoru Hirota

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

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 finetunes 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 results 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.

Original languageEnglish
Pages (from-to)41-54
Number of pages14
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume15
Issue number1
DOIs
Publication statusPublished - Jan 2011
Externally publishedYes

Keywords

  • Congestion
  • Fuzzy logic
  • Particle swarm optimization
  • Wireless LAN

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