Rule Discovery in Alarm Databases

Telecommunication networks produce large amounts of alarm information daily. This data contains potentially valuable knowledge about the network. We present a methodology for the analysis of large telecommunication networks alarm databases. The methods used aim at discovering useful knowledge about the network which can be employed in real time alarm handling software for filtering uninformative alarms, for correlating alarms to construct hypotheses of faults, or for fault prediction. The methodology is based on novel knowledge discovery methods for discovering patterns in alarm databases. We have implemented our methodology in the TASA (Telecommunication Network Alarm Sequence Analyzer) system which discovers patterns in alarm databases and provides tools for interactive identification of the interesting patterns. Computing Reviews Categories and Subject Descriptors: C.2.3 [Computer Systems Organization]: Computer-Communication Networks -- Network Operations H.3.3 [Information Syste..