Performance evaluation with using analytic method in MAC layer for wireless local area networks

In order to increase the Quality of Service (QoS) in wireless local area networks (WLAN), the 802.11e Medium Access Control (MAC) protocol is generally used. Among the parameters affecting the service quality in the MAC protocol, RTS (Request to Send), Threshold Value (RTSTV), Fragmentation Threshold Value (FTV) and Buffer Size (BS) are the most important parameters that affect network performance. In this thesis, RTSTV, FTV and BS input parameters have been optimized with fuzzy logic, Artificial Neural Networks (ANN) and feedback-based control models. In this way, with the IEEE 802.11e Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol, the channel utilization and throughput increased, packet losses and delay are reduced. With the first study with data sets, in WLANs, by using fuzzy logic method, between 36% and 38% improvement in delay, between 2% and 10% improvement in load and between 25% and 44% improvement in throughput were achieved. In the second study, estimation of channel utilization receiver, channel utilization transmitter, data traffic received and data traffic sent were provided with ANN algorithm. In the third study, in order to examine the effect of external factors on QoS in WLANs, the effect of RTSTV, FTV and BS input parameters on channel utilization was examined by adding wireless servers, telecom transmitters and jammers to indoor and outdoor locations according to the position of the nodes. Besides, by using the look-up table with brute force algorithm, the channel utilization has been increased. With the agent structure, which is a new model, the network layer, node layer and process layers have been updated with the timing function and the channel utilization has been increased by 17%. Finally, in the study that also forms the basis of the thesis, by using the feedback controlled method and the embedded fuzzy logic algorithm over Riverbed Models, at the time of simulation the throughput has been increased by 26,48%, the channel utilization has been increased by 2,30%, the data traffic received has been increased by 14,59% and the data traffic sent has been increased by 17,06%. While RTSTV, FTV and BS input parameters are optimized with the feedback controlled algorithm used in these studies; the effects of external parameters such as number of nodes, interarrival time, transmit power, etc. on performance improvements in the new model has been demonstrated with the graphics. All these test results have shown that the new model provides a high rate of performance improvement for WLANs.