Dynamic resource allocation for SDN and edge computing based 5G network

KT Selvi, R Thamilselvan - 2021 Third international conference …, 2021 - ieeexplore.ieee.org
The exponential increase in network traffic leads to considerable stress in 5G
communication. The ultra-high reliability and low latency communication in 5G provides an …

Integrated sensing, computation and communication in B5G cellular Internet of Things

Q Qi, X Chen, C Zhong, Z Zhang - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this article, we investigate the issue of integrated sensing, computation and
communication (SCC) in beyond fifth-generation (B5G) cellular internet of things (IoT) …

An efficient and lightweight predictive channel assignment scheme for multiband B5G-enabled massive IoT: A deep learning approach

S Sakib, T Tazrin, MM Fouda… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Multihop device-to-device (D2D)-enabled relay networks are envisaged to be utilized by the
Internet of Things (IoT) and massive machine-type communication (mMTC) traffic for the …

Performance analysis of intelligent CR-NOMA model for industrial IoT communications

Y Zhang, J Liu, Y Peng, Y Dong… - Computer Modeling in …, 2020 - ingentaconnect.com
Aiming for ultra-reliable low-latency wireless communications required in industrial internet
of things (IIoT) applications, this paper studies a simple cognitive radio non-orthogonal …

Computational intelligence and deep learning for next-generation edge-enabled industrial IoT

S Tang, L Chen, K He, J Xia, L Fan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In this paper, we investigate how to deploy computational intelligence and deep learning
(DL) in edge-enabled industrial IoT networks. In this system, the IoT devices can …

Architecture, generative model, and deep reinforcement learning for IoT applications: Deep learning perspective

S Malik, AK Tyagi, S Mahajan - Artificial Intelligence-based Internet of …, 2022 - Springer
Deep learning is a subclass of machine learning. In the last few years, this has come to
prominence with the core availability of GPUs for computing. There are many applications in …

Big data analytics for 6G-enabled massive internet of things

Z Lv, R Lou, J Li, AK Singh… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The purposes are to enable large-scale Internet of Things (IoT) devices to analyze data
more effectively and provide high-efficiency, low-energy, and wide-coverage technical …

Short-packet communications in wireless-powered cognitive IoT networks: Performance analysis and deep learning evaluation

CD Ho, TV Nguyen, T Huynh-The… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In this paper, we study short-packet communications in wireless-powered cognitive Internet-
of-Things (IoT) networks with multiple primary receivers (PRs). The considered system can …

Machine learning based dynamic cooperative transmission framework for IoUT networks

AAA El-Banna, AB Zaky… - 2019 16th Annual …, 2019 - ieeexplore.ieee.org
Underwater channels are considered challenging media in communication due to the harsh
nature of such environments. However, dynamic transmission can assist in finding sub …

On a novel deep-learning-based intelligent partially overlapping channel assignment in SDN-IoT

F Tang, B Mao, ZM Fadlullah… - IEEE Communications …, 2018 - ieeexplore.ieee.org
Recently, SDN has emerged as a promising technology to cost-effectively provide the scale
and flexibility necessary for IoT services. In this article, we consider the wireless SDN for IoT …