Cellular, wide-area, and non-terrestrial IoT: A survey on 5G advances and the road toward 6G
The next wave of wireless technologies is proliferating in connecting things among
themselves as well as to humans. In the era of the Internet of Things (IoT), billions of …
themselves as well as to humans. In the era of the Internet of Things (IoT), billions of …
Machine learning in IoT security: Current solutions and future challenges
The future Internet of Things (IoT) will have a deep economical, commercial and social
impact on our lives. The participating nodes in IoT networks are usually resource …
impact on our lives. The participating nodes in IoT networks are usually resource …
Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing
Mobile-edge computing (MEC) has emerged as a promising computing paradigm in the 5G
architecture, which can empower user equipments (UEs) with computation and energy …
architecture, which can empower user equipments (UEs) with computation and energy …
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 …
Application management in fog computing environments: A taxonomy, review and future directions
The Internet of Things (IoT) paradigm is being rapidly adopted for the creation of smart
environments in various domains. The IoT-enabled cyber-physical systems associated with …
environments in various domains. The IoT-enabled cyber-physical systems associated with …
Edge content caching with deep spatiotemporal residual network for IoV in smart city
Internet of Vehicles (IoV) enables numerous in-vehicle applications for smart cities, driving
increasing service demands for processing various contents (eg, videos). Generally, for …
increasing service demands for processing various contents (eg, videos). Generally, for …
A survey on computation offloading and service placement in fog computing-based IoT
In recent years, fog computing has emerged as a computing paradigm to support the
computationally intensive and latency-critical applications for resource limited Internet of …
computationally intensive and latency-critical applications for resource limited Internet of …
Distributed deep multi-agent reinforcement learning for cooperative edge caching in internet-of-vehicles
Edge caching is a promising approach to reduce duplicate content transmission in Internet-
of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have …
of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have …
Uav-assisted task offloading for iot in smart buildings and environment via deep reinforcement learning
J Xu, D Li, W Gu, Y Chen - Building and Environment, 2022 - Elsevier
With the rapid development of Internet of Things (IoT) techniques, IoT devices with sensors
have been widely deployed and used in smart buildings and environment, and the …
have been widely deployed and used in smart buildings and environment, and the …
Deep reinforcement learning based resource management for multi-access edge computing in vehicular networks
In this paper, we study joint allocation of the spectrum, computing, and storing resources in a
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …