The rise of traffic classification in IoT networks: A survey
With the proliferation of the Internet of Things (IoT), the integration and communication of
various objects have become a prevalent practice. The huge growth of IoT devices and …
various objects have become a prevalent practice. The huge growth of IoT devices and …
Reinforcement learning for real-time optimization in NB-IoT networks
NarrowBand Internet of Things (NB-IoT) is an emerging cellular-based technology that offers
a range of flexible configurations for massive IoT radio access from groups of devices with …
a range of flexible configurations for massive IoT radio access from groups of devices with …
Novel approach for detection of IoT generated DDoS traffic
The problem of detecting anomalies in network traffic caused by the distributed denial of
service (DDoS) attack so far has mainly been investigated in terms of detection of illegitimate …
service (DDoS) attack so far has mainly been investigated in terms of detection of illegitimate …
Deep reinforcement learning paradigm for performance optimization of channel observation–based MAC protocols in dense WLANs
The potential applications of deep learning to the media access control (MAC) layer of
wireless local area networks (WLANs) have already been progressively acknowledged due …
wireless local area networks (WLANs) have already been progressively acknowledged due …
An overview of smart home iot trends and related cybersecurity challenges
Abstract The Internet of Things (IoT) is a broad concept that encompasses a variety of
technologies and applications. As a result, having a comprehensive understanding of the …
technologies and applications. As a result, having a comprehensive understanding of the …
Reinforcement learning-based ACB in LTE-A networks for handling massive M2M and H2H communications
L Tello-Oquendo, D Pacheco-Paramo… - 2018 IEEE …, 2018 - ieeexplore.ieee.org
Using cellular networks for providing machine-to-machine (M2M) connectivity offers
numerous advantages regarding coverage, deployment costs, security and management …
numerous advantages regarding coverage, deployment costs, security and management …
Deep reinforcement learning-based access class barring for energy-efficient mMTC random access in LTE networks
ATH Bui, AT Pham - IEEE Access, 2020 - ieeexplore.ieee.org
Long-Term Evolution (LTE) networks are expected to be a key enabler for the massive
Machine-Type Communications (mMTC) service in the 5G context. As highly synchronized …
Machine-Type Communications (mMTC) service in the 5G context. As highly synchronized …
Deep reinforcement learning mechanism for dynamic access control in wireless networks handling mMTC
One important issue that needs to be addressed in order to provide effective massive
deployments of IoT devices is access control. In 5G cellular networks, the Access Class …
deployments of IoT devices is access control. In 5G cellular networks, the Access Class …
Delay-aware dynamic access control for mMTC in wireless networks using deep reinforcement learning
D Pacheco-Paramo, L Tello-Oquendo - Computer Networks, 2020 - Elsevier
The success of the applications based on the Internet of Things (IoT) relies heavily on the
ability to process large amounts of data with different Quality-of-Service (QoS) requirements …
ability to process large amounts of data with different Quality-of-Service (QoS) requirements …
Reinforcement learning algorithm for 5G indoor device‐to‐device communications
AG Sreedevi, T Rama Rao - Transactions on Emerging …, 2019 - Wiley Online Library
Abstract Fifth generation (5G), the next generation telecommunications will be striking the
markets in near future. Device‐to‐device (D2D) communication would be a part of 5G to …
markets in near future. Device‐to‐device (D2D) communication would be a part of 5G to …