提出一种面向光传输网络的流量矩阵估计方法.采用压缩感知理论研究光传输网络中的流量矩阵估计,根据信号稀疏表示将流量矩阵稀疏化,基于矩阵变换理论提出新的面向光传输网络的网络层析成像模型.该模型克服了已有网络层析成像模型的病态特性,并通过凸优化来获得流量矩阵的估计等式.提出了具体的估计算法,获得关于光传输网络流量矩阵的精确估计.真实网络的数据仿真表明所提出的方法是有效和可行的.

A traffic matrix estimation approach for optical transportation networks was proposed.Compressive sensing theory was used to study traffic matrix estimation in optical transportation networks.According to the sparse representation of signals,traffic matrix was processed in the sparse way.Matrix transform theory was exploited to present a new network tomography model for optical transportation networks.This model can overcome the illposed nature of the existing network tomography.Conex optimization was used to attain the estimation equation about traffic matrix.The detailed estimation algorithm is presented.The accurate estimation about traffic matrix for optical transportation networks was obtained.The data from the real network was used to perform the simulation.Simulation results show that the proposed method is effective and feasible.