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

SARAIREH, Mohammad, SAATCHI, Reza, AL-KHAYATT, 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.

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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
Research Institute, Centre or Group:	Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Identification Number:	10.1007/s10462-008-9090-5
Depositing User:	Hilary Ridgway
Date Deposited:	20 Dec 2010 10:44
Last Modified:	20 Dec 2010 10:44
URI:	http://shura.shu.ac.uk/id/eprint/2869

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