Jul 2026· 2026 6th International Conference on Intelligent Communications and Computing (ICICC)· pp. 197-200· 0 citations· 6 references
Abstract
This paper proposes a joint optimization algorithm for trajectory control and task offloading ratios based on multi-agent deep reinforcement learning. By jointly optimizing the flight trajectories of unmanned aerial vehicles (UAVs), user scheduling strategies, and task offloading ratios, the decoupled coordination of resource allocation and trajectory planning is achieved, thereby minimizing system delay and weighted energy consumption. An enhanced multi-agent proximal policy optimization algorithm, named FMAHPPO, is designed. Compared with existing benchmark algorithms, the FMAHPPO algorithm significantly reduces the total system overhead and effectively improves the energy efficiency and task processing success rate of multi-UAV swarms. This research provides a valuable theoretical foundation and algorithmic support for the collaborative management of edge resources in future space-air-ground integrated networks (SAGIN).
A Prioritized Adaptive Weighting based on Deep Deterministic Policy Gradient (PAW-DDPG) as an enhanced Deep Deterministic Policy Gradient (DDPG) algorithm to minimize both processing delay and energy consumption by jointly optimizing user scheduling, partial-task offloading, and UAV trajectory is proposed.
W. Saber, Hanan Algamil, Fifi Farouk et al.· Future Internet· 0 citations
The rapid growth of Internet of Vehicles (IoV) applications has imposed strict requirements on low-latency and energy-efficient computing services. This letter investigates a multi-Uncrewed Aerial Vehicle (UAV)-assisted IoV system, where multiple Mobile Edge Computing (MEC)-enabled UAVs (MUs) collaboratively provide co...
Yong-Bin Wang, Peng Lin, Yan Liu et al.· IEEE Wireless Communications...· 0 citations
To enable efficient and rational task offloading within the UAV swarm, a matching game‐based task offloading algorithm is proposed, and its stability and convergence are theoretically proven.
Ting Lyu, Yong Heng, Hao Zhang et al.· Concurrency and Computation· 0 citations
— Unmanned Aerial Vehicles (UAVs) have emerged as flexible relay platforms capable of enhancing wireless connectivity in beyond-5G and 6G networks. This paper investigates the joint optimization of UAV trajectory and power allocation to maximize end-to-end throughput under practical mobility and power constraints. The...
Trang Thi Quynh Pham· Journal of Communications· 0 citations
Simulation of three typical UAV dispatching problems shows that greedy algorithm has better optimization in resource utilization and the convergence of the simulated annealing algorithm is better under the complex constraints.
Jiaming Wang, Jing Guo, Ning Du et al.· SAE technical paper series· 0 citations
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