Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges
Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
A GNN-based supervised learning framework for resource allocation in wireless IoT networks
The Internet of Things (IoT) allows physical devices to be connected over the wireless
networks. Although device-to-device (D2D) communication has emerged as a promising …
networks. Although device-to-device (D2D) communication has emerged as a promising …
Reinforcement and deep reinforcement learning for wireless Internet of Things: A survey
Nowadays, many research studies and industrial investigations have allowed the integration
of the Internet of Things (IoT) in current and future networking applications by deploying a …
of the Internet of Things (IoT) in current and future networking applications by deploying a …
Deep learning for intelligent IoT: Opportunities, challenges and solutions
Next-generation wireless networks have to be robust and self-sustained. Internet of things
(IoT) is reshaping the technological adaptation in the daily life of human beings. IoT …
(IoT) is reshaping the technological adaptation in the daily life of human beings. IoT …
Machine learning for smart environments in B5G networks: Connectivity and QoS
SH Alsamhi, FA Almalki, H Al-Dois… - Computational …, 2021 - Wiley Online Library
The number of Internet of Things (IoT) devices to be connected via the Internet is
overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and …
overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and …
Intelligent traffic adaptive resource allocation for edge computing-based 5G networks
The popularity of smart mobile devices has led to a tremendous increase in mobile traffic,
which has put a considerable strain on the fifth generation of mobile communication …
which has put a considerable strain on the fifth generation of mobile communication …
Resource allocation based on deep reinforcement learning in IoT edge computing
By leveraging mobile edge computing (MEC), a huge amount of data generated by Internet
of Things (IoT) devices can be processed and analyzed at the network edge. However, the …
of Things (IoT) devices can be processed and analyzed at the network edge. However, the …
Resource allocation in uplink NOMA-IoT networks: A reinforcement-learning approach
Non-orthogonal multiple access (NOMA) exploits the potential of the power domain to
enhance the connectivity for the Internet of Things (IoT). Due to time-varying communication …
enhance the connectivity for the Internet of Things (IoT). Due to time-varying communication …
Deep reinforcement learning for Internet of Things: A comprehensive survey
The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …
communication, computing, caching and control (4Cs) problems. The recent advances in …
iRAF: A deep reinforcement learning approach for collaborative mobile edge computing IoT networks
Recently, as the development of artificial intelligence (AI), data-driven AI methods have
shown amazing performance in solving complex problems to support the Internet of Things …
shown amazing performance in solving complex problems to support the Internet of Things …