DRL-assisted delay optimized task offloading in automotive-industry 5.0 based VECNs

DRL-assisted delay optimized task offloading in automotive-industry 5.0 based VECNs

The rapid growth of Automotive-Industry 5.0 and its emergence with beyond fifth-generation (B5G) communications, is making vehicular edge computing networks (VECNs) increasingly complex. The latency constraints of modern automotive applications make it difficult to run complex applications on vehicl...

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Bibliographic Details
Main Authors:	Muhammad Ayzed Mirza, Junsheng Yu, Salman Raza, Moez Krichen, Manzoor Ahmed, Wali Ullah Khan, Khaled Rabie, Thokozani Shongwe
Format:	Article
Language:	English
Published:	Elsevier 2023-06-01
Series:	Journal of King Saud University: Computer and Information Sciences
Subjects:	Automotive-Industry 5.0 Vehicular Edge Computing (VEC) Task offloading Beyond fifth-generation (B5G) Deep Reinforcement Learning (DRL)
Online Access:	http://www.sciencedirect.com/science/article/pii/S1319157823000423

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