SARAIREH, M., SAATCHI, R., ALKHAYATT, S. and STRACHAN, R. (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.
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.
|Additional Information:||Times Cited: 0|
|Research Institute, Centre or Group:||Materials and Engineering Research Institute > Centre for Robotics and Automation > Mobile Machine and Vision Laboratory|
|Depositing User:||Danny Weston|
|Date Deposited:||13 Apr 2010 15:34|
|Last Modified:||23 Sep 2010 11:35|
Actions (login required)
Downloads per month over past year