Cognitive selection mechanism performance in IEEE 802.11 WLAN
Recent growth in Wireless Local Area Network (WLAN) usage has generated considerable interest in the establishment of the IEEE 802.11 WLAN standards. WLAN has been developed with the capability to handle tremendous growth of data traffic and therefore have been proliferating worldwide. The infl...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
International Association of Computer Science and Information Technology Press
2013
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/35629/ http://irep.iium.edu.my/35629/ http://irep.iium.edu.my/35629/ http://irep.iium.edu.my/35629/2/aliah_j.pdf |
| Summary: | Recent growth in Wireless Local Area Network
(WLAN) usage has generated considerable interest in the
establishment of the IEEE 802.11 WLAN standards. WLAN
has been developed with the capability to handle tremendous
growth of data traffic and therefore have been proliferating
worldwide. The influencing factors and the parameters
involved prior choosing which access point (AP) to connect
with are to be carefully evaluated and dealt with in the process
of WLAN deployment. Properly designed selection
mechanisms that able to provide not only radio coverage but
also a good internet connection speed are in turn expected to be
able to improve the Quality of Service (QoS). In this paper, a
new approach for the AP selection in IEEE 802.11 is proposed.
The new technique takes into account internet connection
speed in contrast to the classic approach that solely based on
the Received Signal Strength (RSS). A heuristic selection model
was developed namely Evaluative AP Selection which used
LINUX Bash script programming whilst the internet
connection speed test was ran by means of PHP script. The
results for the selection were evaluated respectively to see the
variation in selection pattern when compared to the default
selection algorithm. The time interval during the scanning and
selection process was also analysed in the investigation to
further identify the performance of the model. The
enhancement reaped from the developed selection algorithm is
expected to bring benefit to different user at various places |
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