Wi-Fi meets ML: A survey on improving IEEE 802.11 performance with machine learning

S Szott, K Kosek-Szott, P Gawłowicz… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Wireless local area networks (WLANs) empowered by IEEE 802.11 (Wi-Fi) hold a dominant
position in providing Internet access thanks to their freedom of deployment and configuration …

A study on the channel bonding in IoT networks: Requirements, applications, and challenges

D Kandar, P Chyne, S Nath Sur… - International journal of …, 2023 - Wiley Online Library
The most well‐known sort of remote Internet connection is wireless local area networks
(WLANs) due to its unsophisticated operation and deployment. Subsequently, the quantity of …

Adaptive Data Placement in Multi-Cloud Storage: A Non-Stationary Combinatorial Bandit Approach

L Li, J Shen, B Wu, Y Zhou, X Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Multi-cloud storage is recently a viable approach to solve the vendor lock-in, reliability, and
security issues in cloud storage systems. As a key concern, data placement influences the …

Multi-armed bandits for spectrum allocation in multi-agent channel bonding WLANs

S Barrachina-Muñoz, A Chiumento, B Bellalta - IEEE Access, 2021 - ieeexplore.ieee.org
While dynamic channel bonding (DCB) is proven to boost the capacity of wireless local area
networks (WLANs) by adapting the bandwidth on a per-frame basis, its performance is tied …

Improving Spatial Reuse of Wireless LANs using Contextual Bandits

H Kim, G Na, H Im, J So - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
Spatial reuse is an important factor in building highly efficient wireless local area networks.
The key to maximizing spatial reuse is to support concurrent transmissions while avoiding …

An Enhanced Ensemble Learning Method for Sentiment Analysis based on Q-learning

M Savargiv, B Masoumi, MR Keyvanpour - Iranian Journal of Science and …, 2024 - Springer
Ensemble learning is a powerful technique for combining multiple classifiers to achieve
improved performance. However, the challenge of applying ensemble learning to dynamic …

Reinforcement Learning-Based Power Control for MACA-Based Underwater MAC Protocol

F Ahmed, J Cho, E Shitiri, HS Cho - IEEE Access, 2022 - ieeexplore.ieee.org
A major amount of the energy of battery-powered sensors is spent during packet
transmissions. This issue has led to the development of power-control-based multiple …

[PDF][PDF] Contribution to the development of Wi-Fi networks through machine learning based prediction and classification techniques

SS Shaabanzadeh, J Sánchez-González - grcm.tsc.upc.edu
The growing number of Wi-Fi users and the emergence of bandwidth-intensive services
have necessitated an increase in Access Point (AP) density, resulting in more complex …

A Distributed Wi-Fi Channel Assignment Method with Channel Bonding Considering the Number of Associated Users

K Kinoshita, Y Aihara, M Kishida - 2022 23rd Asia-Pacific …, 2022 - ieeexplore.ieee.org
In recent years, with spread of smartphones, the amount of mobile data traffic is growing
rapidly. To support such traffic, more and more Wi-Fi access points (APs) are deployed and …

[PDF][PDF] Echoing the Future: On-Device Machine Learning in Next-Generation Networks-A Comprehensive Survey

HB Pasandi, FB Pasandi, F Parastar, A Moradbeikie… - researchgate.net
On-device Machine Learning (on-deviceML) is the concept of bringing Machine Learning
models to the constraint device itself and making it smarter. Tiny Machine Learning (TinyML) …