光通信技术2026，Vol.50Issue(3)：36-40,5.DOI:10.13921/j.cnki.issn1002-5561.2026.03.006
基于SAC的低轨卫星光网络负载均衡路由优化算法
Load-balancing routing optimization algorithm for low earth orbit satellite optical networks based on SAC
摘要
Abstract
To address the issues of network load imbalance and communication delay caused by satellite dynamics and complex environmental factors,a load-balancing routing optimization algorithm for low earth orbit Satellite optical network based on Soft Actor-Critic(SAC)in deep reinforcement learning(DRL)is proposed.By simulating the satellite network environment and dynamically adjusting decision-making strategies,the algorithm achieves dynamic optimization of routing paths,aiming to ra-tionally allocate network resources and improve network performance.Simulation results demonstrate that the proposed algo-rithm exhibits significant advantages in optimizing data flow distribution and enhancing system reliability.Under traffic intensi-ties of 50%and 100%,the average link load rate is optimized by 29.9%and 42.0%,respectively,while routing delay is also ef-fectively reduced.关键词
负载均衡/深度强化学习/低轨卫星光网络/路由优化/卫星互联网Key words
load balancing/deep reinforcement learning/low earth orbit satellite optical network/routing optimization/satel-lite internet分类
信息技术与安全科学引用本文复制引用
唐可意,李志刚..基于SAC的低轨卫星光网络负载均衡路由优化算法[J].光通信技术,2026,50(3):36-40,5.基金项目
中国电子科技集团公司第三十四研究所发展基金项目(K134002024SH02)资助. （K134002024SH02）
