Artificial Intelligence Review

, Volume 27, Issue 2–3, pp 95–111 | Cite as

Assessment and improvement of quality of service in wireless networks using fuzzy and hybrid genetic-fuzzy approaches

  • Mohammad Saraireh
  • Reza Saatchi
  • Samir Al-khayatt
  • Rebecca Strachan
Article

Abstract

Fuzzy and hybrid genetic-fuzzy approaches were used to assess and improve quality of service (QoS) in simulated wireless networks. Three real-time audio and video applications were transmitted over the networks. The QoS provided by the networks for each application was quantitatively assessed using a fuzzy inference system (FIS). Two methods to improve the networks’ QoS were developed. One method was based on a FIS mechanism and the other used a hybrid genetic-fuzzy system. Both methods determined an optimised value for the minimum contention window (CWmin) in IEEE 802.11 medium access control (MAC) protocol. CWmin affects the time period a wireless station waits before it transmits a packet and thus its value influences QoS. The average QoS for the audio and video applications improved by 42.8% and 14.5% respectively by using the FIS method. The hybrid genetic-fuzzy system improved the average QoS for the audio and video applications by 35.7% and 16.5% respectively. The study indicated that the devised methods were effective in assessing and significantly improving QoS in wireless networks.

Keywords

Fuzzy logic Hybrid genetic-fuzzy logic Quality of service Wireless networks Multimedia transmission 

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Mohammad Saraireh
    • 1
  • Reza Saatchi
    • 2
  • Samir Al-khayatt
    • 2
  • Rebecca Strachan
    • 2
  1. 1.Faculty of Engineering/Computer Engineering DepartmentMutah UniversityMutahJordan
  2. 2.Faculty of ACESSheffield Hallam UniversitySheffieldUK

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