Multi-agent multi-armed bandit learning for offloading delay minimization in v2x networks
NH Nguyen, P Le Nguyen, H Dinh… - 2021 IEEE 19th …, 2021 - ieeexplore.ieee.org
In a three-tier Vehicle to X (V2X) network, a vehicle can offload the computational tasks to
the edge computing component at a roadside unit (RSU) or a base station with cloud …
the edge computing component at a roadside unit (RSU) or a base station with cloud …
Deep reinforcement learning-based offloading for latency minimization in 3-tier v2x networks
Multi-access edge computing (MEC) is seen as an effective technique for decreasing service
latency in a V2X network by offloading computational activities. With MEC, a three-tier …
latency in a V2X network by offloading computational activities. With MEC, a three-tier …
Adaptive learning-based multi-vehicle task offloading
In vehicular mobile edge computing, vehicles can provide computing services via V2V
communication. Vehicles offload the task to the vehicles which own computing resources at …
communication. Vehicles offload the task to the vehicles which own computing resources at …
Multi-armed bandit based task offloading by probabilistic V2X communication in vehicle edge cloud system
J Xie, Q Si, Y Tang - 2020 IEEE 91st Vehicular Technology …, 2020 - ieeexplore.ieee.org
Compared with traditional cloud computing, service providers in edge computing are closer
to the requester of the demand, and can better meet the requirements of communication …
to the requester of the demand, and can better meet the requirements of communication …
Learning iov in edge: deep reinforcement learning for edge computing enabled vehicular networks
The development of artificial intelligence, wireless communication and smart sensor platform
facilities the emergence of multitude of novel vehicular applications in recent years. These …
facilities the emergence of multitude of novel vehicular applications in recent years. These …
Cooperative multi-player multi-armed bandit: Computation offloading in a vehicular cloud network
In recent years, computation offloading has been considered as a promising technology to
support computation-intensive vehicular applications. In this paper, we mainly focus on …
support computation-intensive vehicular applications. In this paper, we mainly focus on …
Adaptive task offloading in V2X networks based on deep reinforcement learning
D Yang, B Ni, H Qin, F Ma - International Conference on …, 2022 - spiedigitallibrary.org
With the constraints of limited computing and communication resources in V2X networks,
V2V communication for task offloading needs to adapt to the dynamic V2X environment …
V2V communication for task offloading needs to adapt to the dynamic V2X environment …
Deep reinforcement learning-based computation offloading in vehicular networks
L Geng, H Zhao, H Liu, Y Wang… - 2021 8th IEEE …, 2021 - ieeexplore.ieee.org
With the rapid development of 5G communications and the Internet of Things (IoT), vehicular
networks have enriched people's lives with abundant applications. Since most of such …
networks have enriched people's lives with abundant applications. Since most of such …
Modeling and minimizing latency in three-tier v2x networks
P Le Nguyen, RH Hwang, PM Khiem… - … 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
Leveraging mobile cloud computing (MCC) and mobile edge computing (MEC) for
offloading computational tasks is a promising approach to enabling delay-sensitive …
offloading computational tasks is a promising approach to enabling delay-sensitive …
Distributed computation offloading using deep reinforcement learning in internet of vehicles
In this paper, we first take the moving vehicles as a RP (resource pool), by which we
proposed a distributed computation offloading scheme to fully utilize the available resources …
proposed a distributed computation offloading scheme to fully utilize the available resources …