基于模糊参考模型机制的网络自适应拥塞控制

在高速通信网络的发展过程中，业务流呈现出的突发性和多样性为提高网络服务质量制造了更多的困难。该文提出的网络自适应拥塞控制方法以模糊参考模型机制的核心来提高主动队列管理算法在突发性网络状况中的适应能力，以2条信息通道分别实现主动队列管理的控制与学习功能，并结合参考模型机制实现模糊反向推理算法，针对网络突发性状况自适应调整主控制通道的控制行为。仿真研究表明，该控制方法提高了拥塞控制机制的自适应性能，并在自适应性能和实时性能上获得了较好的平衡。

Network Adaptive Congestion Control Based on Fuzzy Reference Model Mechanism

In the development of high speed communication network, the burst state and diversity of network traffic make it difficult to achieve QoS of network. This paper proposes a network adaptive congestion control method, where the fuzzy reference model mechanism is integrated to improve the adaptive performance of AQM in the burst network. The control system is integrated with the reference model to implement the fuzzy back-loop inference learning algorithm, and adjust the control behavior of the primary control channel following the network burst state. Simulation results show that the proposed method improves the performance of the congestion control system greatly, and makes a better trade-off between the adaptive performance and real-time performance.