Offloading mechanisms based on reinforcement learning and deep learning algorithms in the fog computing environment

DH Abdulazeez, SK Askar - Ieee Access, 2023‏ - ieeexplore.ieee.org
Fog computing has emerged as a computing paradigm for resource-restricted Internet of
things (IoT) devices to support time-sensitive and computationally intensive applications …

Network slicing based learning techniques for iov in 5g and beyond networks

W Hamdi, C Ksouri, H Bulut… - … Surveys & Tutorials, 2024‏ - ieeexplore.ieee.org
The effects of transport development on people's lives are diverse, ranging from economy to
tourism, health care, etc. Great progress has been made in this area, which has led to the …

[HTML][HTML] A comprehensive survey on reinforcement-learning-based computation offloading techniques in edge computing systems

D Hortelano, I de Miguel, RJD Barroso… - Journal of Network and …, 2023‏ - Elsevier
In recent years, the number of embedded computing devices connected to the Internet has
exponentially increased. At the same time, new applications are becoming more complex …

[HTML][HTML] IRATS: A DRL-based intelligent priority and deadline-aware online resource allocation and task scheduling algorithm in a vehicular fog network

B Jamil, H Ijaz, M Shojafar, K Munir - Ad hoc networks, 2023‏ - Elsevier
Cloud computing platforms support the Internet of Vehicles, but the main bottlenecks are
high latency and massive data transmission in cloud-based processing. Vehicular fog …

Artificial intelligence in 6G wireless networks: Opportunities, applications, and challenges

A Alhammadi, I Shayea, AA El-Saleh… - … Journal of Intelligent …, 2024‏ - Wiley Online Library
Wireless technologies are growing unprecedentedly with the advent and increasing
popularity of wireless services worldwide. With the advancement in technology, profound …

[HTML][HTML] Optimal energy management strategies for hybrid electric vehicles: A recent survey of machine learning approaches

JJ Jui, MA Ahmad, MMI Molla, MIM Rashid - Journal of Engineering …, 2024‏ - Elsevier
Abstract Hybrid Electric Vehicles (HEVs) have emerged as a viable option for reducing
pollution and attaining fuel savings in addition to reducing emissions. The effectiveness of …

Machine learning for next‐generation intelligent transportation systems: A survey

T Yuan, W da Rocha Neto… - Transactions on …, 2022‏ - Wiley Online Library
Intelligent transportation systems, or ITS for short, includes a variety of services and
applications such as road traffic management, traveler information systems, public transit …

Toward the age of intelligent vehicular networks for connected and autonomous vehicles in 6g

VL Nguyen, RH Hwang, PC Lin, A Vyas… - IEEE …, 2022‏ - ieeexplore.ieee.org
Twenty-two years after the advent of the first-generation vehicular network, that is, dedicated
short-range communications (DSRC) standard/IEEE 802.11 p, the vehicular technology …

Security of 6G-enabled vehicle-to-everything communication in emerging federated learning and blockchain technologies

M Kim, I Oh, K Yim, M Sahlabadi, Z Shukur - IEEE Access, 2023‏ - ieeexplore.ieee.org
Sixth-generation (6G) communication is emerging as a seamless and massive connection of
almost all digital devices. Vehicles, which are extensively linked with human mobility, must …

Artificial Intelligence techniques to mitigate cyber-attacks within vehicular networks: Survey

A Haddaji, S Ayed, LC Fourati - Computers and Electrical Engineering, 2022‏ - Elsevier
Rapid advancements in communication technology have made vehicular networks a reality
with numerous applications. However, vehicular network security is still an open research …