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Cited 2 time in webofscience Cited 5 time in scopus
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Smart adaptive collision avoidance for IEEE 802.11open access

Authors
Edalat, YaldaObraczka, KatiaAhn, Jong-Suk
Issue Date
Jan-2022
Publisher
Elsevier BV
Keywords
IEEE 802; 11; Congestion avoidance; CSMA; CA; Machine learning; Enabling; disabling RTS; CTS
Citation
Ad Hoc Networks, v.124, pp 1 - 15
Pages
15
Indexed
SCIE
SCOPUS
Journal Title
Ad Hoc Networks
Volume
124
Start Page
1
End Page
15
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/3721
DOI
10.1016/j.adhoc.2021.102721
ISSN
1570-8705
1570-8713
Abstract
In this paper, we introduce a novel algorithm that uses machine learning to dynamically decide whether to enable or disable IEEE 802.11 DCF's RTS/CTS. Our algorithm continuously learns current networking conditions, namely air time, i.e. the ratio between the size of data/control information being transmitted and transmission rate, and network contention to compare the cost between using RTS/CTS or retransmitting data, and dynamically switches RTS/CTS on and off accordingly. Simulation results using a variety of WLANas well as wireless multi-hop ad-hoc network scenarios, including synthetic and real traffic traces, demonstrate that the proposed approach consistently outperforms current best practices, such as never enabling RTS/CTS or using a pre-specified threshold to decide whether to switch RTS/CTS on or off.
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College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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