A study of Real-time fault detecting system using information filtering technique

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Expansion in scale and speed are the most important features of Internet. Establishing an effective way for fault management becomes the main topic for this computer networks. In this research, we proposed a new system for real-time fault detecting in large scale computer network. We first constructed a traffic monitoring system for collecting the error packets from network traffic flow. Then, we proposed a new algorithm, called Dynamic Symptom Isolation Algorithm, to detect the network fault packets in an effective way, in which filtering technique is applied to suppress the detected error symptom, so that the small fault existing behind the large number faults in the network could be found thoroughly. Our experiments showed that the new system's performance is as twice as the conventional system for detecting faults symptoms in large network environment..