Unmanned aerial vehicle task offloading method and device for low-orbit satellite network, electronic device and storage medium

By constructing a joint optimization model and a Lyapunov optimization framework, and combining deep neural networks for online decision-making, the problems of long-term energy consumption and resource cost management in low-Earth orbit satellite networks were solved, and stable and efficient task offloading was achieved.

CN122496094BActive Publication Date: 2026-09-15HANGZHOU INNOVATION RES INST OF BEIJING UNIV OF AERONAUTICS & ASTRONAUTICS +2
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Patent Information

Application Number
CN202610968556.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-07-01
Publication Date
2026-09-15
Estimated Expiration
2046-07-01

AI Technical Summary

Technical Problem

Traditional low-Earth orbit satellite network mission offloading methods have failed to effectively manage long-term computing energy consumption and resource costs, resulting in unstable operation of satellite networks over long time scales and exceeding budget for terrestrial network resource usage, triggering service throttling or tariff penalties.

Method used

A joint optimization model is constructed with the goal of maximizing the long-term average task unloading volume. By using a virtual computational energy consumption queue and a virtual resource wholesale cost queue, combined with the Lyapunov optimization framework, the long-term constraint is transformed into a single-slot static optimization problem, and a deep neural network is used for online decision optimization.

Benefits of technology

Without relying on prior information about future missions, it has achieved effective management of high mission offloading volume and long-term energy consumption and cost constraints of satellite networks over long periods of time, ensuring stable system operation and economic sustainability of resources.

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Abstract

Embodiments of the present application provide a UAV task offloading method and device for a low-orbit satellite network, electronic equipment and storage medium, relating to the technical field of communication. Based on the low-orbit satellite network, a joint optimization model is constructed with the goal of maximizing the long-term average task offloading amount, a virtual computing energy consumption queue is constructed for the long-term average computing energy consumption constraint, and a virtual resource wholesale cost queue is constructed for the long-term average cost constraint. Based on the Lyapunov optimization framework, the joint optimization model is converted into a single-time-slot static optimization problem. In each time slot, according to the UAV task arrival state and the virtual queue backlog state of the current time slot, the single-time-slot static optimization problem is solved to obtain the service deployment decision, the computing resource allocation decision and the task offloading decision to the ground network of the time slot. Thus, the satellite network can effectively maintain a high task offloading amount in long-time continuous operation.
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