基于包络特征的IDC网络自适应流量调控方法

Adaptive Traffic Control Method of IDC Network Based on Envelope Feature

传统流量调控方法不能自动调整约束规则,导致面对不同流量密度时,容易出现较大的带宽损失率,因此基于包络特征,研究一种全新的IDC网络自适应流量调控方法。该方法构建IDC网络流量能耗模型,提取包络特征并获取流量空间分布状态,根据网络内部信息流向设置调控自适应约束规则,应用BP神经网络改进IDC网络自适应流量调控的实现。实验结果表明在random20、random40、random60这3种不同流量密度测试条件下,所研究方法的吞吐率较高,带宽损失率低,适用于调控IDC网络自适应流量。

The traditional traffic control method can not automatically adjust the constraint rules,which leads to a large bandwidth loss rate when facing different traffic density.Therefore,based on the envelope feature,a new adaptive traffic control method for IDC network is studied.This method constructs the IDC network flow energy consumption model,extracts the envelope characteristics,obtains the flow spatial distribution state and sets the regulation adaptive constraint rules according to the network internal information flow direction,and applies the BP neural network to improve realization of the IDC network adaptive flow regulation.Experimental results show that under the conditions of random20,random40 and random60,the throughput and bandwidth loss rate of the proposed method are high,and it is suitable to control the adaptive traffic of IDC network.