Research On Internet Service Fault Diagnosis Algorithm

As Internet migrates gradually to SOA (Service Oriented Architecture), Service Providers (SP) find out that Internet services have the potential to bring great profits. Thus various Internet services appeared in recent decades, such as VoIP, IPTV, VoD, Internet Game, VPN and etc. In order to maintain traditional customers and attract new users, SP should provide QoS (Quality of Service) for their services.Fault management is crucial for QoS guarantee, since service unavailability or performance degradation may cause Service Level Agreement (SLA) violation, which will affect the SP's credit and cause the financial loss. Therefore, in order to shorten the unavailable and performance degradation period when a service failure happens, SP needs service oriented fault management to localize the fault and take counter measures. This dissertation focuses on the fault management architecture for Internet services and the related algorithms. Probability theory based fault diagnosis, FPM (fault propagation model) modeling, fault localization algorithms analysis and improvement, and the multi-domain fault management framework for Internet services are examined in this dissertation. The main contributions are as follows:(1) The complicated causes of Internet services failure are analyzed. Based on the comparison of current fault diagnosis techniques, probability theory is chosen to be the theoretical tool and Hidden Markov Model is employed as the FPM for Internet services. A HMM based FPM with the modeling approach is proposed. By dividing the fault management task into separated layers, the layering model can simplify the fault diagnosis process.(2) Process based on Hidden Markov (HMM) of the fault propagation model (FPM), a new generation of fault propagation model in the modeling process, failure to consider the relationship between the transfer, taking into account fault with the transfer of relations between symptoms. Between failures for the transfer to the outside world are not visible, that is not directly determine the fault components. Therefore, the problem of fault diagnosis can be described as symptoms in the observation of known component failure under the premise of the process of reasoning.(3) Network for the reality of the difficulty of access to data, probe selection and fault will be assumed that reasoning through the combination of information entropy in the HMM, the proposed prior to the - to the algorithms (Forward-backward) algorithm, will probe into the choice of model parameters to obtain the process go, so that the model assumptions and fault reasoning study to become an organic whole.(4) Through the largest information entropy gain probe set guidelines for minimum coverage, reasonable reduction in diagnostic probe generated network load. Reasoning part of the fault hypothesis, the incomplete information under the Viterbi N-best method, through sequencing, to retain partial function prior to the first N records, recursive manner calculated, and reach to the global optimum.