A joint optimization approach using SOCP for UAV trajectories, DRL-LLM for resource scheduling, and LP for offloading achieves higher task success rates and system efficiency than multi-agent RL baselines in simulated dense urban IoV environments.
Mobile edge computing: A survey on architec- ture and computation offloading
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Joint Optimization of Trajectory Control, Resource Allocation, and Task Offloading for Multi-UAV-Assisted IoV
A joint optimization approach using SOCP for UAV trajectories, DRL-LLM for resource scheduling, and LP for offloading achieves higher task success rates and system efficiency than multi-agent RL baselines in simulated dense urban IoV environments.