Research On Fault Detection And Diagnosis Technology Based On Multi-layer Networks

With the rapid development of network technology and hardware facilities,the Internet has made a significant influence on people's study,work and life.Generally,daily used networks are composed of multiple single-layer networks which are interconnected.Different layers have different network properties and structures,but they are interdependent.This complex network is called a multi-layer network.In recent years,network virtualization technology has become increasingly mature.Researchers have proposed SDN(Software Defined Network)to simplify network management.SDN is a new type of multi-layer network architecture.As the influence of the network continues to deepen,the security performance requirements of the network are becoming higher and higher.How to quickly detect the network status and locate the fault to reduce the impact of the fault on network performance is of great significance.In this thesis,fault detection and diagnosis based on multi-layer networks is studied.It includes the following three aspects:(1)Overview of multi-layer networks technology.Based on the research of the traditional multi-layer networks and SDN,the main fault diagnosis algorithms of traditional network and SDN are compared.The advantages,existing problems and applicable scope of each algorithm are analyzed.(2)Fault diagnosis algorithm of traditional multi-layer networks.The fault diagnosis algorithms of traditional network are mostly applicable to single-layer networks and the related researches are mature enough.However,researches on fault diagnosis applicable to multi-layer networks are relatively rare.The fault diagnosis algorithms of single-layer networks cannot be applied to multi-layer networks directly because of the different properties between layers and the characteristics of multi-layer networks.According to the fact that most networks only contain a small number of faults,MIU(Malti-layer Iterative Update)algorithm is proposed.First of all,the Bayesian network is used to analyze the fault propagation mechanism of the multi-layer network and a fault propagation model of the multi-layer network is established.Then,a heuristic possible fault hypothesis algorithm is proposed for the single-layer network in view of the few faults fact.Finally,based on the characteristics of the network and the relationship between the layers in the multi-layer network,a method for iterating the possible fault hypothesis in the multi-layer network is proposed,and the most probable fault hypothesis is calculated.The experimental results show that the proposed algorithm is superior to the other algorithms in time performance on the premise of the few faults,and the algorithm performs well in fault diagnosis and misdiagnosis.(3)Fault diagnosis algorithm of SDN.At present,the network shall be measured on a large scale according to most fault diagnosis algorithms of SDN,and the analysis of the location of the fault is completed in the view of the measurement results.However,such method occupies a large amount of network resources and is inefficient.GMP(Greedy Minimum Probes)algorithm with rapid detection and location is proposed in this thesis.First of all,a rule management server is used to monitor all controllers and handle control-layer faults.Afterwords,network topology information is obtained through the controllers.In the next part,a greedy method is used to obtain test sets to quickly detect the network status according to the results of the topology information and the headspace analysis.Finally,based on the detection results and the number of suspicious rules in the network,an algorithm for accurately locating faults is proposed.Through simulation experiments,it is proved that the algorithm proposed in this thesis has smaller network overhead and can meet the requirements of rapid network detection and accurate fault location.