信息熵在网络流量矩阵估算中的应用

Application of Information Entropy in Network Traffic Matrix Estimation

提出一种网络流量矩阵估算方法,在已知网络拓扑结构和网络链路流量的情况下,根据网络链路流量计算出信息熵,利用期望最大化算法对网络源和目的对之间的流量需求进行估计。以校园网为实验环境,对骨干网络采集网络流量数据,与通用重力模型方法的比较结果表明,利用该方法进行估算有更高的准确性。

This paper presents a network traffic matrix estimation method.In the situation of giving the network topology and link traffic,it computes the information entropy according to the link traffic,and utilizes Expectation Maximization（EM） algorithm to compute the traffic demand of the pair of Origin and Destination（OD）.The method is evaluated by an experiment on campus networks.Traffic data collected on the backbone network prove that,compared with Generalized Gravity Model（GGM）,the method has higher accuracy.