Joint Optimization of Trajectory Control, Resource Allocation, and Task Offloading for Multi-UAV-Assisted IoV
📰 ArXiv cs.AI
Learn to optimize trajectory control, resource allocation, and task offloading for multi-UAV-assisted IoV systems to minimize delay and energy consumption
Action Steps
- Decouple complex non-convex optimization problems into hierarchical execution frameworks
- Apply Second-Order Cone Programming (SOCP) to solve sequential distributed optimization algorithms
- Design and implement task offloading systems for multi-UAV-assisted IoV
- Optimize trajectory control and resource allocation to minimize system delay and energy consumption
- Evaluate and compare the performance of different optimization algorithms for IoV systems
Who Needs to Know This
This research benefits teams working on IoT, UAV, and optimization problems, particularly those in the fields of computer science, engineering, and operations research
Key Insight
💡 Decoupling complex optimization problems into hierarchical frameworks can improve system efficiency
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Optimize multi-UAV-assisted IoV systems for minimal delay & energy consumption #IoV #UAV #Optimization
Key Takeaways
Learn to optimize trajectory control, resource allocation, and task offloading for multi-UAV-assisted IoV systems to minimize delay and energy consumption
Full Article
Title: Joint Optimization of Trajectory Control, Resource Allocation, and Task Offloading for Multi-UAV-Assisted IoV
Abstract:
arXiv:2605.04436v1 Announce Type: cross Abstract: This paper investigates a multi-Unmanned Aerial Vehicle (UAV) joint base station-assisted Internet of Vehicles (IoV) task offloading system in dense urban environments. To minimize system delay and energy consumption under strict coupling constraints, the complex non-convex optimization problem is decoupled into a hierarchical execution framework. First, a sequential distributed optimization algorithm based on Second-Order Cone Programming (SOCP)
Abstract:
arXiv:2605.04436v1 Announce Type: cross Abstract: This paper investigates a multi-Unmanned Aerial Vehicle (UAV) joint base station-assisted Internet of Vehicles (IoV) task offloading system in dense urban environments. To minimize system delay and energy consumption under strict coupling constraints, the complex non-convex optimization problem is decoupled into a hierarchical execution framework. First, a sequential distributed optimization algorithm based on Second-Order Cone Programming (SOCP)
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