Software Defined
Software-defined networking (SDN) aims to improve network management and flexibility by centralizing control over network devices. Current research heavily focuses on applying machine learning, particularly deep learning (including LSTM, GRU, GNN, and reinforcement learning variants like DQN and PPO) to optimize various aspects, such as intelligent routing, intrusion detection, and resource allocation. These advancements enhance network performance, security, and adaptability, impacting both the efficiency of network operations and the development of more robust and secure network architectures.
Papers
An Intelligent SDWN Routing Algorithm Based on Network Situational Awareness and Deep Reinforcement Learning
Jinqiang Li, Miao Ye, Linqiang Huang, Xiaofang Deng, Hongbing Qiu, Yong Wang
Intelligent multicast routing method based on multi-agent deep reinforcement learning in SDWN
Hongwen Hu, Miao Ye, Chenwei Zhao, Qiuxiang Jiang, Yong Wang, Hongbing Qiu, Xiaofang Deng