改进的基于最大似然的快速拓扑估计方法

基于最大似然的网络拓扑估计方法能够获得全局最优的估计结果，优于一般局部最优化和节点对融合方法，但在网络规模较大时存在计算复杂度较高的缺点。首先证明了网络拓扑估计似然函数是单峰的（即只有一个极值）且峰值为最大值；然后利用单峰特征，改进了现有基于最大似然的拓扑估计方法，在最大似然树搜索过程中无需返回到似然值小的状态，降低了计算复杂度。最后，Matlab和ns-2仿真结果证明在不降低拓扑估计准确率的情况下，改进的算法将计算复杂度减少了30%~46%.

Improved fast topology estimation method based on maximum likelihood

Maximum likelihood based topology estimation method can obtain globally optimal estimation results,and its performance is better than that of other methods such as general local optimization and node fusion method.However,when network scale is large,the topology estimation is computationally intensive.To solve this problem,firstly,the authors proved that the network topology estimation likelihood function is a single-peaked function and the peak value is maximum value.Using the single-peaked property of lik...