A Class of Active Queue Management Algorithm Based on BP Neural Network

摘要：

As an end-to-end congestion control mechanism, Active Queue Management (AQM) technology maintains smaller queue length and higher link utilization through discarding packets in intermediate network nodes. This paper discussed some previous AQM algorithms, RED, BLUE and RLGD, and found out shortcomings in which by comparing with them. On the Basis of Artificial Intelligence (AI) theory and technology, a new AQM algorithm based on BP neural network is proposed. In the end, the implement of the new Active Queue Management algorithm is presented, and the convergence is proved.

关键词： Active Queue Management Congestion control RED BP neural network

作者: Wu Junxin Liu Jianchang Guo Zhe

作者单位: School of Information Science and Engineering, Northeastern University, Shenyang 110004

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 1580-1583

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）