A game-based computation offloading method in vehicular multiaccess edge computing networks
Multiaccess edge computing (MEC) is a new paradigm to meet the requirements for low
latency and high reliability of applications in vehicular networking. More computation …
latency and high reliability of applications in vehicular networking. More computation …
Resource allocation for delay-sensitive vehicle-to-multi-edges (V2Es) communications in vehicular networks: A multi-agent deep reinforcement learning approach
The rapid development of internet of vehicles (IoV) has recently led to the emergence of
diverse intelligent vehicular applications such as automatic driving, auto navigation, and …
diverse intelligent vehicular applications such as automatic driving, auto navigation, and …
Asynchronous deep reinforcement learning for collaborative task computing and on-demand resource allocation in vehicular edge computing
Vehicular Edge Computing (VEC) is enjoying a surge in research interest due to the
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …
Joint computing and caching in 5G-envisioned Internet of vehicles: A deep reinforcement learning-based traffic control system
Recent developments of edge computing and content caching in wireless networks enable
the Intelligent Transportation System (ITS) to provide high-quality services for vehicles …
the Intelligent Transportation System (ITS) to provide high-quality services for vehicles …
QoE-driven edge caching in vehicle networks based on deep reinforcement learning
C Song, W Xu, T Wu, S Yu, P Zeng… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The Internet of vehicles (IoV) is a large information interaction network that collects
information on vehicles, roads and pedestrians. One of the important uses of vehicle …
information on vehicles, roads and pedestrians. One of the important uses of vehicle …
Cooperative edge caching with location-based and popular contents for vehicular networks
In this article, we propose a cooperative edge caching scheme, which allows vehicles to
fetch one content from multiple caching servers cooperatively. In specific, we consider two …
fetch one content from multiple caching servers cooperatively. In specific, we consider two …
Deep reinforcement learning-based adaptive computation offloading for MEC in heterogeneous vehicular networks
H Ke, J Wang, L Deng, Y Ge… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The vehicular network needs efficient and reliable data communication technology to
maintain low latency. It is very challenging to minimize the energy consumption and data …
maintain low latency. It is very challenging to minimize the energy consumption and data …
Optimal UAV caching and trajectory in aerial-assisted vehicular networks: A learning-based approach
In this article, we investigate the UAV-aided edge caching to assist terrestrial vehicular
networks in delivering high-bandwidth content files. Aiming at maximizing the overall …
networks in delivering high-bandwidth content files. Aiming at maximizing the overall …
Deep reinforcement learning for collaborative edge computing in vehicular networks
Mobile edge computing (MEC) is a promising technology to support mission-critical
vehicular applications, such as intelligent path planning and safety applications. In this …
vehicular applications, such as intelligent path planning and safety applications. In this …
UAV/HAP-assisted vehicular edge computing in 6G: Where and what to offload?
In the context of 6th Generation (6G) networks, Vehicular Edge Computing (VEC) is
emerging as a promising solution to let battery-powered ground vehicles with limited …
emerging as a promising solution to let battery-powered ground vehicles with limited …