A comprehensive survey of the key technologies and challenges surrounding vehicular ad hoc networks

Z **a, J Wu, L Wu, Y Chen, J Yang, PS Yu - ACM Transactions on …, 2021 - dl.acm.org
Vehicular ad hoc networks (VANETs) and the services they support are an essential part of
intelligent transportation. Through physical technologies, applications, protocols, and …

[Retracted] Deep and Reinforcement Learning Technologies on Internet of Vehicle (IoV) Applications: Current Issues and Future Trends

L Elmoiz Alatabani, E Sayed Ali… - Journal of Advanced …, 2022 - Wiley Online Library
Recently, artificial intelligence (AI) technology has great attention in transportation systems,
which led to the emergence of a new concept known as Internet of Vehicles (IoV). The IoV …

Edge-enabled two-stage scheduling based on deep reinforcement learning for internet of everything

X Zhou, W Liang, K Yan, W Li, I Kevin… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Nowadays, the concept of Internet of Everything (IoE) is becoming a hotly discussed topic,
which is playing an increasingly indispensable role in modern intelligent applications. These …

Ubiquitous computation in internet of vehicles for human-centric transport systems

I Ullah, F Ali, H Khan, F Khan, X Bai - Computers in Human Behavior, 2024 - Elsevier
Abstract The Internet of Vehicles (IoV) has the potential to bring about a revolutionary
transformation in transportation through its influence on human behavior and interactions …

Task scheduling mechanisms for fog computing: a systematic survey

M Hosseinzadeh, E Azhir, J Lansky, S Mildeova… - IEEE …, 2023 - ieeexplore.ieee.org
In the Internet of Things (IoT) ecosystem, some processing is done near data production
sites at higher speeds without the need for high bandwidth by combining Fog Computing …

Wireless powered metaverse: Joint task scheduling and trajectory design for multi-devices and multi-UAVs

X Wang, J Li, Z Ning, Q Song, L Guo… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
To support the running of human-centric metaverse applications on mobile devices,
Unmanned Aerial Vehicle (UAV)-assisted Wireless Powered Mobile Edge Computing …

The applicability of reinforcement learning methods in the development of industry 4.0 applications

T Kegyes, Z Süle, J Abonyi - Complexity, 2021 - Wiley Online Library
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …

Unmanned era: A service response framework in smart city

Y Hui, Z Su, TH Luan - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
The autonomous vehicles (AVs) in smart city, as intelligent mobile robots, are expected to
provide diversified services to facilitate the life of citizens. However, the attributes of the …

LACCVoV: Linear adaptive congestion control with optimization of data dissemination model in vehicle-to-vehicle communication

AK Sangaiah, JS Ramamoorthi… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Vehicle-to-vehicle communication assists road-side information exchange granting ease of
access and sharing between users. The communication between the vehicles is short-lived …

Intelligent task allocation for mobile crowdsensing with graph attention network and deep reinforcement learning

C Xu, W Song - IEEE Transactions on Network Science and …, 2023 - ieeexplore.ieee.org
Mobile crowdsensing (MCS) leverages crowd intelligence, ie, smart devices and their
owners, to collect data in an intelligent and cost-efficient manner. One of the fundamental …