自动化学报2026，Vol.52Issue(4)：709-723,15.DOI:10.16383/j.aas.c250413
基于分层策略强化学习的多类型流量差异化路由优化
Differentiated Routing Optimization for Multi-type Traffic Based on Hierarchical Policy Reinforcement Learning
赵之栩 1刘坤 1王璐瑶 1夏元清1
作者信息
- 1. 北京理工大学自动化学院自主智能无人系统全国重点实验室 北京 100081
- 折叠
摘要
Abstract
Routing is an important method for optimizing network resource allocation.However,traditional rout-ing algorithms rely on static strategies to optimize single quality of service metrics,making it difficult to address the differentiated requirements of explosive growth in multi-type traffic.Although deep reinforcement learning has provided new ideas for routing optimization in dynamic network environments,existing methods still lack fine-grained perception of traffic types and cannot flexibly adjust routing strategies.To this end,this paper designs a traffic-aware routing algorithm based on hierarchical policy reinforcement learning for the differentiated routing re-quirements of different traffic types.First,a traffic classification module is introduced to achieve fine-grained per-ception of the differentiated service requirements of different traffic.Second,graph convolutional networks are used to efficiently model the network topology,based on which a hierarchical decision network and a differentiated re-ward function are designed to guide the agent to generate adaptive routing decisions and realize dynamic adjust-ment of routing strategies for each traffic category.Meanwhile,a global attention mechanism is introduced into the actor-critic framework to enhance the agent's ability to model the spatio-temporal dependency of network states,and the training efficiency and stability are improved through generalized advantage estimation and proximal policy optimization algorithms.Finally,the effectiveness of the proposed algorithm is verified on various network topologies.关键词
多类型流量/深度强化学习/注意力机制/差异化路由/QoS优化Key words
multi-type traffic/deep reinforcement learning/attention mechanism/differentiated routing/quality of service optimization引用本文复制引用
赵之栩,刘坤,王璐瑶,夏元清..基于分层策略强化学习的多类型流量差异化路由优化[J].自动化学报,2026,52(4):709-723,15.
