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). pp. 95-111. ISSN 0269-2821

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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
Subjects:	G700 Artificial Intelligence
Department:	Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User:	EPrint Services
Date Deposited:	14 Aug 2009 12:00
Last Modified:	13 Oct 2019 00:24
URI:	http://nrl.northumbria.ac.uk/id/eprint/2734

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