通信学报2026，Vol.47Issue(7)：65-79,15.DOI:10.11959/j.issn.1000-436x.TXXB250694
面向智能体互联网的AIGC任务分布式自适应智能卸载策略
Distributed adaptive intelligent offloading strategies for AIGC tasks in the Internet of agents
摘要
Abstract
The Internet of agents environment imposes high computational demands and requires dynamic quality of ser-vice(QoS)for artificial intelligence generated content(AIGC)tasks,an intelligent computational offloading strategy based on PPO was proposed.Firstly,a two-dimensional joint action space encompassing offloading location decisions and generation quality level selection was constructed to accommodate the scalable characteristics of AIGC tasks.Sec-ondly,a quality of experience reward function integrating user preference modes was designed.Furthermore,to address training instability caused by dimensional discrepancies in the multidimensional state space,a dual online normalization mechanism for states and rewards was introduced,which was combined with a dynamic learning rate scheduling strategy to enhance the algorithm's feature extraction efficiency in complex environments.Simulation results demonstrate that the proposed algorithm significantly outperforms baseline algorithms in terms of convergence speed and stability.关键词
智能体互联网/边缘侧大模型/移动边缘计算/深度强化学习/人工智能生成内容Key words
Internet of agents/edge-based large model/mobile edge computing/deep reinforcement learning/AIGC分类
信息技术与安全科学引用本文复制引用
袁晓铭,张馨灵,邓庆绪,李长乐,王嘉诚,策力木格..面向智能体互联网的AIGC任务分布式自适应智能卸载策略[J].通信学报,2026,47(7):65-79,15.基金项目
国家自然科学基金资助项目(No.62371116) （No.62371116）
河北省自然科学基金优秀青年科学基金资助项目(No.F2026501042) （No.F2026501042）
大数据智能分析与行业应用湖北省重点实验室开放基金(湖北大学)资助项目(No.2025BDIAA03) （湖北大学）
河北省教育厅在读研究生创新能力培养基金资助项目(No.CXZZSS2026175) The National Natural Science Foundation of China(No.62371116),Hebei Natural Science Fund for Excellent Young Scientists(No.F2026501042),Open Fund of Hubei Key Laboratory of Big Data Intelligent Analysis and Industrial Applica-tions(Hubei University)(No.2025BDIAA03),Hebei Provincial Department of Education Funding Program for Cultivating Innova-tive Ability of Postgraduate Students(No.CXZZSS2026175) （No.CXZZSS2026175）
