Multi-parameters Link Failure Localization Algorithm Based on Compressive Sensing

To improve the performance and decrease the constraints of fault localization with single distinguish parameter, a multi-parameters link failure localization algorithm is proposed based on compressive sensing and entropy difference. Firstly it makes a fast fault prediction by Bayesian network, then it introduces a parameter named fault coverage and selects probable link failure using compressive sensing, finally defines fault information entropy difference and obtains the root fault based on the parameter. The simulation results show that the predicted fault set can be compressed and the selected probable fault set contains the true fault, meanwhile the proposed algorithm achieves high detection rate and low false positive rate.