| Autor: |
Hacı Bayram KARAKURT, Cemal KOÇAK |
| Jazyk: |
English<br />Turkish |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Gazi Üniversitesi Fen Bilimleri Dergisi, Vol 8, Iss 3, Pp 542-560 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2147-9526 |
| DOI: |
10.29109/gujsc.707916 |
| Popis: |
Channel efficiency in wireless local area networks (WLAN) is crucial for performance. One of the most important parameters that increase channel efficiency is channel utilization (CU). Channel Utilization has an important function to increase the Quality of Service (QoS) in the medium access control (MAC) layer of wireless local area networks (WLAN). There are many input parameters to measure the channel utilization in WLANs. Most popular input parameters, Request to Send Threshold (RTS Threshold-RTSTV), Fragmentation Threshold (FTV) and Buffer Size (BS) controls the usage and movement of RTS and CTS virtual packets used in CSMA/CA (Carrier-sense Multiple Access with Collision Avoidance) protocol to increase Channel Utilization. In previous studies, these parameters were tested on OPNET Modeler and datasets were obtained. Performance is increased in the output parameters by applying reinforcement learning over the obtained datasets. In this study, RTSTV, FTV and BS values were updated using the brute force algorithm in with the Look-up Table on the code block structure of the OPNET Modeler and the Channel Utilization increased at the time of simulation. With this new agent model structure, the network layer, node layer and process layer have been updated. With this simulation study, CU and performance has been increased with reinforcement learning from %10 to 15% -18%. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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