Study Of Datamining Application In Telecommunication Alarm

Alarm correlation system is currently dealing with alarm flow in fault management of telecommunication network management. It's an expert system, which is used for analyzing alarms. Telecommunication network is so complicated that it is hard to build an alarm correlation system for one special network.There are lots of alarm data in telecommunication alarm database. A lot of usable information are contained in these data, which reveal the status of telecommunication network. Alarm data is very suitable for KDD application and the result of application can be used to improve the fault management of telecommunication network.According to this situation, this paper proposes to use datamining technology for the analysis of alarm data. The main works and contributions in this paper are as follows:⑴A Datamining Model in telecommunication alarm is presented in this paper.⑵Datamining System Model for telecommunication alarm database is also presented. ⑶We describe a serial of methods for solving problems in the discovery of recurrent patterns of alarms in database. The whole process of datamining is also described in this paper, including data collection and preprocessing, rule discovery, rule postprocessing and application. Some resolutions are given for relative existing problem.⑷While Apriori algorithm is used for datamining on alarm data, It will generate large number of candidate frequent itemsets. To avoid this weakness, we describe and extend FP_growth algorithm in association rule discovery in alarm data. New Algorithm is more scalable and effective.⑸We extend the current episodes rule discovery algorithm and make it be able to find episodes rule with two time bound and be applicable for large set database.