Congestion Control of TCP Network Using a Self-Recurrent Wavelet Neural Network

자기회귀 웨이블릿 신경 회로망을 이용한 TCP 네트워크 혼잡제어

In this paper, we propose the design of active queue management (AQM) control system using the self-recurrent wavelet neural network (SRWNN). By regulating the queue length close to reference value, AQM can control the congestions in TCP network. The SRWNN is designed to perform as a feedback controller for TCP dynamics. The parameters of network are tunes to minimize the difference between the queue length of TCP dynamic model and the output of SRWNN using gradient-descent method. We evaluate the performances of the proposed AQM approach through computer simulations.