Applications of machine learning in networking: a survey of current issues and future challenges
Communication networks are expanding rapidly and becoming increasingly complex. As a
consequence, the conventional rule-based algorithms or protocols may no longer perform at …
consequence, the conventional rule-based algorithms or protocols may no longer perform at …
Deep learning for wireless networking: The next frontier
With the growth of mobile technology in the last decade, wireless networks have become an
integral part of our everyday lives. To meet the increasingly stringent application …
integral part of our everyday lives. To meet the increasingly stringent application …
Complementing IIoT services through AI: Feasibility and suitability
F Banaie, M Hashemzadeh - AI-Enabled Threat Detection and Security …, 2021 - Springer
Abstract Intelligent Industrial IoT (IIoT) is a promising tool in the context of the fourth
industrial revolution, Industry 4.0. It is reliant on the interaction between computer-integrated …
industrial revolution, Industry 4.0. It is reliant on the interaction between computer-integrated …
Experimental measurement of the capacity region of wireless networks
Y Thomas, N Smyrnioudis… - 2021 19th International …, 2021 - ieeexplore.ieee.org
We present a method for experimentally measuring the capacity region of a wireless
network, defined here as the set of all possible combinations of simultaneously achievable …
network, defined here as the set of all possible combinations of simultaneously achievable …
Time-distributed feature learning in network traffic classification for Internet of Things
YSK Manjunath, S Zhao… - 2021 IEEE 7th World …, 2021 - ieeexplore.ieee.org
The plethora of Internet of Things (IoT) devices leads to explosive network traffic. The
network traffic classification (NTC) is an essential tool to explore behaviours of network …
network traffic classification (NTC) is an essential tool to explore behaviours of network …
Federated user activity analysis via network traffic and deep neural network in mobile wireless networks
L Guo, S Wang, J Yin, Y Wang, J Yang, G Gui - Physical Communication, 2021 - Elsevier
User activity analysis (UAA) is a promising technology for network management and network
security via network traffic. Recently, deep learning (DL) has been applied into network …
security via network traffic. Recently, deep learning (DL) has been applied into network …
Network Flow Classification and Volume Prediction using Novel Ensemble Deep Learning Architectures in the Era of the Internet of Things (IoT)
Network flow and volume optimization have become a challenging task with the rapid
growth of IoT devices. Fortunately, network flow classification and network volume prediction …
growth of IoT devices. Fortunately, network flow classification and network volume prediction …
Deep reinforcement learning for scheduling in multi-hop wireless networks
The efficient scheduling of transmission links in a wireless network with a certain
optimization objective and subject to the interference and network flow constraints plays a …
optimization objective and subject to the interference and network flow constraints plays a …
Multi-agent deep reinforcement learning for request dispatching in distributed-controller software-defined networking
Recently, distributed controller architectures have been quickly gaining popularity in
Software-Defined Networking (SDN). However, the use of distributed controllers introduces …
Software-Defined Networking (SDN). However, the use of distributed controllers introduces …
Convolutional neural network for relays selection in the Internet of Vehicles
M Bersali, A Rachedi, H Bouarfa - … International Conference on …, 2021 - ieeexplore.ieee.org
Developing smart systems and strategies to transfer data effectively is a crucial challenge
with a rising number of connected automobiles and objects in the Internet of Vehicles (IoV) …
with a rising number of connected automobiles and objects in the Internet of Vehicles (IoV) …