The Research Of SDH Transmission Network Warning Processes Analysis System

With the development of communication network, the intelligent network management technology is required. At present, the equipment firms all use systems which support their own network management, and these systems are independent and unable to communicate mutually. They also have no way to cooperate. A uniformly synthetical system for network management is urgently required.Knowledge can be gained automatically by using knowledge discovery and data mining. Malfunction management is an important part of network management. The paper mines the correlation relationship of transport alarms by building transfers models and using methods of knowledge discovery. The thesis implements the improvement of Apriori algorithm for mining correlation of SDH alarms. With the improved algorithm, the data of SDH alarms is correlated, and then the received rules are compressed. The finally received rules contain more information than the general alarms have, and is easier. They are helpful to find the important alarms and analyze them. The experiment proved that the time and spacial complexity of the algorithm is acceptable.