Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …
intelligence tool is widely researched to intelligentize communication and networking …
Machine and deep learning for resource allocation in multi-access edge computing: A survey
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
RL/DRL meets vehicular task offloading using edge and vehicular cloudlet: A survey
The last two decades have seen a clear trend toward crafting intelligent vehicles based on
the significant advances in communication and computing paradigms, which provide a safer …
the significant advances in communication and computing paradigms, which provide a safer …
Price and risk awareness for data offloading decision-making in edge computing systems
G Mitsis, EE Tsiropoulou… - IEEE Systems …, 2022 - ieeexplore.ieee.org
The proliferation of multiaccess edge computing (MEC) paradigm has created a challenging
multiuser–multiserver–multiaccess edge computing competitive environment, which brings …
multiuser–multiserver–multiaccess edge computing competitive environment, which brings …
A probabilistic approach for cooperative computation offloading in MEC-assisted vehicular networks
Mobile edge computing (MEC) has been an effective paradigm for supporting computation-
intensive applications by offloading resources at network edge. Especially in vehicular …
intensive applications by offloading resources at network edge. Especially in vehicular …
A distributed algorithm for task offloading in vehicular networks with hybrid fog/cloud computing
Fog computing has been an effective paradigm of real-time applications in the IoT area,
which enables task offloading at network edge devices. Particularly, many emerging …
which enables task offloading at network edge devices. Particularly, many emerging …
Asynchronous deep reinforcement learning for data-driven task offloading in MEC-empowered vehicular networks
Mobile edge computing (MEC) has been an effective paradigm to support real-time
computation-intensive vehicular applications. However, due to highly dynamic vehicular …
computation-intensive vehicular applications. However, due to highly dynamic vehicular …
DNN partition and offloading strategy with improved particle swarm genetic algorithm in VEC
C Li, L Chai, K Jiang, Y Zhang, J Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a novel computing paradigm, which is designed to
satisfy the growing computation and communication needs of vehicle systems. With the …
satisfy the growing computation and communication needs of vehicle systems. With the …
Accelerating dnn inference with reliability guarantee in vehicular edge computing
This paper explores on accelerating Deep Neural Network (DNN) inference with reliability
guarantee in Vehicular Edge Computing (VEC) by considering the synergistic impacts of …
guarantee in Vehicular Edge Computing (VEC) by considering the synergistic impacts of …
Artificial Intelligence and Machine Learning as key enablers for V2X communications: A comprehensive survey
M Christopoulou, S Barmpounakis, H Koumaras… - Vehicular …, 2023 - Elsevier
The automotive industry is undergoing a profound digital transformation to create
autonomous vehicles. Vehicle-to-Everything (V2X) communications enable the provisioning …
autonomous vehicles. Vehicle-to-Everything (V2X) communications enable the provisioning …