Smart adaptive collision avoidance for IEEE 802.11open access
- Authors
- Edalat, Yalda; Obraczka, Katia; Ahn, 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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- Appears in
Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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