SARAIREH, Mohammed, SAATCHI, Reza, ALKHAYATT, Samir and STRACHAN, Rebecca (2007). Assessment and improvement of quality of service in wireless networks using fuzzy and hybrid genetic-fuzzy approaches. Artificial intelligence review, 27 (2-3), 95-111.
Full text not available from this repository.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 (CW (min)) in IEEE 802.11 medium access control (MAC) protocol. CW (min) 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.
Item Type: | Article |
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Additional Information: | Times Cited: 0 |
Research Institute, Centre or Group - Does NOT include content added after October 2018: | Cultural Communication and Computing Research Institute > Communication and Computing Research Centre Materials and Engineering Research Institute > Modelling Research Centre > Microsystems and Machine Vision Laboratory |
Identification Number: | https://doi.org/10.1007/s10462-008-9090-5 |
Page Range: | 95-111 |
Depositing User: | Danny Weston |
Date Deposited: | 13 Apr 2010 14:34 |
Last Modified: | 18 Mar 2021 09:45 |
URI: | https://shura.shu.ac.uk/id/eprint/1669 |
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