Predicting failures of computer systems: a case study for a telecommunication system

Authors:
Felix Salfner;Michael Schieschke;Miroslaw Malek
Affiliations:
Institut für Informatik, Humboldt-Universität zu Berlin, Berlin, Germany;Institut für Informatik, Humboldt-Universität zu Berlin, Berlin, Germany;Institut für Informatik, Humboldt-Universität zu Berlin, Berlin, Germany
Venue:
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Year:
2006

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Abstract

The goal of online failure prediction is to forecast imminent failures while the system is running. This paper compares Similar Events Prediction (SEP) with two other well-known techniques for online failure prediction: a straightforward method that is based on a reliability model and Dispersion Frame Technique (DFT). SEP is based on recognition of failure-prone patterns utilizing a semi-Markov chain in combination with clustering. We applied the approaches to real data of a commercial telecommunication system. Results are presented in terms of precision, recall, F-measure and accumulated runtime-cost. The results suggest a significantly improved forecasting performance.