东华大学学报（英文版）2026，Vol.43Issue(4)：59-66,8.DOI:10.19884/j.1672-5220.202502002
基于可再生能源供应的多层无人水面艇移动边缘计算系统:任务卸载与资源分配优化
Joint Optimization of Task Offloading and Resource Allocation for Multi-Layer USV-MEC System with Renewable Energy Supply
摘要
Abstract
Mobile edge computing(MEC)plays a vital role in supporting communication,computation,and resource management within the maritime industry.It has become an essential element in the advancement of maritime technology.This study adopts a space-air-sea integrated MEC network,in which high-altitude platforms(HAPs)and low-earth orbit(LEO)satellites powered by renewable energy assist unmanned surface vehicles(USVs)in task offloading.The goal of this study is to minimize the total energy consumption of the system subject to a controllable task backlog queue.The Lyapunov optimization method is adopted to transform the original stochastic optimization problem into a deterministic optimization problem,thereby ensuring the stability of the system.Furthermore,an algorithm based on convex optimization is proposed,which is specifically designed to optimize transmission power allocation and channel allocation.The simulation results verify that the proposed scheme can significantly reduce the total energy consumption of the system compared with other benchmark schemes.关键词
Lyapunov优化/无人水面艇/凸优化/移动边缘计算Key words
Lyapunov optimization/unmanned surface vehicle/convex optimization/mobile edge computing分类
信息技术与安全科学引用本文复制引用
黄海,罗萍,吕子龙,张文倩..基于可再生能源供应的多层无人水面艇移动边缘计算系统:任务卸载与资源分配优化[J].东华大学学报（英文版）,2026,43(4):59-66,8.基金项目
National Natural Science Foundation of China(No.62301307) （No.62301307）
Shanghai Pujiang Program,China(No.23PJD041) （No.23PJD041）
Chenguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission,China(No.CGA60) （No.CGA60）
AI-Enhanced Research Program of Shanghai Municipal Education Commission,China(No.SMEC-AI-DHUY-10) （No.SMEC-AI-DHUY-10）
