Title: Adaptive energy-efficient task offloading and resource management in UAV-assisted mobile edge networks using dynamic DRL

Authors: Yunfeng Zhou; Hong Cao; Jiateng Duan; Haohua Qing; Amin Mohajer

Addresses: Guangzhou College of Commerce, Guangzhou, Guangdong 511363, China ' Guangzhou Modern Information Engineering College, Guangzhou, Guangdong 510663, China ' Guangzhou College of Commerce, Guangzhou, Guangdong 511363, China ' Department of Applied Computing and Artificial Intelligence, Faculty of Computing, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia ' Department of Electrical and Computer Engineering, The University of British Columbia (UBC), Vancouver, BC V6T 1Z4, Canada

Abstract: Next-generation aerial edge networks must support delay-critical and computation-intensive services in highly dynamic wireless environments. This paper introduces a distributed control architecture that integrates flight-aware workload distribution, predictive mobility mapping, and adaptive edge resource slicing. The model combines spatiotemporal learning with an enhanced policy gradient mechanism for joint optimisation of service placement, bandwidth provisioning, and UAV trajectory scheduling. By integrating predictive modelling of user mobility via recurrent neural structures and embedding temporal attention, the system anticipates regional demand fluctuations and proactively reconfigures aerial coverage. A dual-critic actor-learner structure ensures stable policy evolution under hybrid discrete-continuous action spaces. Extensive evaluations across diverse network densities and traffic dynamics reveal that the proposed scheme improves task finalisation rates by over 30%, sustains autonomous operation via harvested energy, and consistently outperforms existing baselines in spectral efficiency and decision latency. These findings position the framework as a robust foundation for real-time orchestration in scalable, mission-adaptive aerial edge infrastructures.

Keywords: UAV-enabled edge intelligence; predictive mobility modelling; spatiotemporal resource orchestration; policy-driven task offloading; dynamic edge slicing.

DOI: 10.1504/IJSNET.2025.148198

International Journal of Sensor Networks, 2025 Vol.48 No.4, pp.212 - 226

Received: 18 Oct 2024
Accepted: 08 May 2025
Published online: 29 Aug 2025 *

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