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M. Wastian, M. Landsiedl, F. Breitenecker:
"A Soft Computing Model for Server Outage Detection";
Simulation Notes Europe, 25 (2015), 1; S. 27 - 34.

Abstract. Several approaches to detect or even predict
abnormal events as early as possible will be discussed.
The model input is a time series of frequently collected
data. The approaches presented in this document use
various methods originating in the field of data mining,
machine learning and soft computing in a hybrid manner.
After a basic introduction including several areas of
application, the focus will lie on the modular parts of the
proposed server outage model, starting with a discussion
about different approaches to time series prediction
such as SARIMA models and specific artificial neural
networks. After the presentation of several algorithms
for outlier detection (angle-based outlier factor, oneclass
support vector machines) the gained results of the
simulation are put up for discussion. The text ends with
an outlook for possible future work.

http://dx.doi.org/10.11128/sne.25.tn.102277