摘要
研究动态网络中间节点的拥塞控制.提出一种PID型神经网络的主动队列管理(AQM)算法,给出基于BP学习规则的网络参数自调整规律,根据Lyapunov定理证明了系统的稳定性.基于NS-2平台的仿真结果表明,该算法适应瞬息万变的网络环境,系统稳态误差和响应速度等指标优于PID算法.
To study the congestion control of intermediate nodes in the changing network, PID type neural network control scheme for AQM (active queue management) is proposed. Back-propagation algorithm is used to adjust the weights of neural networks and stability of closed-loop system is proved according to the Lyapunov theory. Based on NS-2 simulation platform, the result showed that the proposed control scheme can adapt to the changing network situation, the system steady-state error and transient performance of the proposed scheme is superior to those of PID.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2006年第10期892-896,共5页
Transactions of Beijing Institute of Technology
基金
国家自然科学基金资助项目(60474033)