Using Neural Networks for Alarm
Correlation in Cellular Phone Networks
Hermann Wietgrefe, Klaus-Dieter Tuchs, Klaus Jobmann,
Guido Carls, Peter Fröhlich, Wolfgang Nejdl, Sebastian Steinfeld
Abstract
Alarm handling and especially alarm correlation tools are necessary to
manage large telecommunication networks. In this paper we describe our
neural network based alarm correlation system, which uses a Cascade
Correlation neural network to correlate alarms in a GSM network. The
results of our approach called Cascade Correlation Alarm Correlator
(CCAC) are shown. The behaviour in the case of noisy data is discussed
and compared in detail to a codebook approach. Furthermore we contrast
the neural network approach to another solution developed by our group
which uses model-based diagnosis.
Keywords: Mobile Networks, Network Management,
Fault-Management, Alarm Correlation, Cascade Correlation Neural
Networks, Model-Based Diagnosis, Codebook
The full paper is available as a postscript file
.