天地一体化信息网络2025，Vol.6Issue(4)：1-8,8.DOI:10.11959/j.issn.1000-0801.2025034
基于强化学习的天地融合网络算力路由发展与挑战
Development and Challenges of Computing Power Routing in Space-Ground Integrated Networks Based on Reinforcement Learning
摘要
Abstract
Space-air-ground integrated networks(SAGIN)establish a multi-dimensional communication architecture by synergistically coordinating satellites,aerial platforms,and terrestrial facilities.The inherent characteristics of dynamic topologies and heterogeneous computing resources within this architecture present novel challenges for routing mechanisms.In response to this complex scenario,re-inforcement learning(RL)has emerged as a prominent research focus for addressing computing-aware routing problems,owing to its robust environmental adaptability and intelligent decision-making capabilities.This paper systematically reviews and investigates the application of RL in computing-aware routing.It analyzes the core design principles from the dual perspectives of algorithmic para-digms and optimization objectives.Finally,this paper deeply analyzes and prospectively identifies the key challenges that RL faces in the context of SAGIN environments.关键词
天地融合/算力路由/强化学习Key words
space-integrated-ground/computing power routing/reinforcement learning分类
信息技术与安全科学引用本文复制引用
WANG Mingqian,WU Xiaomei,YANG Guang,LEI Guangwang,ZHANG Tingting,LIU Zishen..基于强化学习的天地融合网络算力路由发展与挑战[J].天地一体化信息网络,2025,6(4):1-8,8.基金项目
国家自然科学基金(No.62401047)The National Natural Science Foundation of China(No.62401047) （No.62401047）
