Edge-driven resource allocation in vehicular networks: A joint framework of multi-agent reinforcement learning and demand-supply predictive modeling
With the advent of connected and autonomous vehicles, addressing the diverse Quality of Service (QoS) requirements and limited bandwidth in heterogeneous vehicular networks has become a critical challenge. To tackle these issues, a collaborative edge-enabled demand-and-supply resource allocation str...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025021723 |
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