Hierarchical Reinforcement Learning for Multi-Layer Multi-Service Non-Terrestrial Vehicular Edge Computing

Hierarchical Reinforcement Learning for Multi-Layer Multi-Service Non-Terrestrial Vehicular Edge Computing

Vehicular Edge Computing (VEC) represents a novel advancement within the Internet of Vehicles (IoV). Despite its implementation through Road Side Units (RSUs), VEC frequently falls short of satisfying the escalating demands of Vehicle Users (VUs) for new services, necessitating supplementary computa...

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Bibliographic Details
Main Authors: Swapnil Sadashiv Shinde, Daniele Tarchi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Machine Learning in Communications and Networking
Subjects:
Vehicular networks
edge computing
non-terrestrial networks
computation offloading
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/10609447/
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https://ieeexplore.ieee.org/document/10609447/

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