Optimizing Energy Efficiency in Vehicular Edge-Cloud Networks Through Deep Reinforcement Learning-Based Computation Offloading

Vehicular Edge-Cloud Computing (VECC) paradigm has emerged as a viable approach to overcome the inherent resource limitations of vehicles by offloading computationally demanding tasks to remote servers. Despite its potential, existing offloading strategies often result in increased latency and sub-o...

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Hlavní autoři:	Ibrahim A. Elgendy, Ammar Muthanna, Abdullah Alshahrani, Dina S. M. Hassan, Reem Alkanhel, Mohamed Elkawkagy
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2024-01-01
Edice:	IEEE Access
Témata:	Autonomous vehicles energy efficiency load balancing computation offloading vehicular edge-cloud computing task caching
On-line přístup:	https://ieeexplore.ieee.org/document/10788691/
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