Intelligent Driving Task Scheduling Service in Vehicle-Edge Collaborative Networks Based on Deep Reinforcement Learning

With the evolution of 6G technology, mobile edge computing is rapidly advancing as a crucial application scenario. This research presents an innovative method for vehicle-edge task offloading decision-making, leveraging real-time data inputs such as channel conditions, image entropy, and detector co...

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Veröffentlicht in:	IEEE eTransactions on network and service management 2024-08, Vol.21 (4), p.4357-4368
Hauptverfasser:	Wang, Nuanlai, Pang, Shanchen, Ji, Xiaofeng, Wang, Min, Qiao, Sibo, Yu, Shihang
Format:	Artikel
Sprache:	eng
Schlagworte:	6G Internet of Vehicles 6G mobile communication Algorithms Collaboration collaborative computing Computation offloading Computational modeling Confidence intervals Decision making Deep learning deep reinforcement learning Edge computing Lightweight Machine learning Mobile computing Optimization Processor scheduling Real time Servers Task analysis task offloading Task scheduling Weight reduction
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