Rule Discovery in Alarm Databases

Kimmo Hätönen, Mika Klemettinen, Heikki Mannila, Pirjo Ronkainen, and Hannu Toivonen: Rule Discovery in Alarm Databases. Report C-1996-7, Department of Computer Science, University of Helsinki, March 1996. 19 pages. <http://www.cs.helsinki.fi/TR/C-1996/7>

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Abstract

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.

Index Terms

Categories and Subject Descriptors:
C.2.3 [Computer Systems Organization]: Computer-Communication Networks - Network Operations
H.3.3 [Information Systems]: Information Storage and Retrieval - Information Search and Retrieval
H.5.2 [Information Systems]: Information Interfaces and Presentation - User Interfaces
I.2.6 [Computing Methodologies]: Artificial Intelligence - Learning

General Terms: Algorithms, Human Factors, Management

Additional Key Words and Phrases: Telecommunication Network Alarms, Data Mining, Knowledge Discovery, Discovery Methodology, Episodes, Association Rules, Alarm Correlation