FernUni spezial

Probabilistic Fault Management in Distributed Systems

Fault management has to face the uncertain and incomplete management information and dynamic changes in distributed systems. In this book, Bayesian networks are applied to model the dependencies among managed objects and to provide efficient methods for locating the root causes of failures arising from inaccurate management information. A Strongest Dependence Route (SDR) algorithm is offered to trace the strongest dependency route from effects and to identify the sequence of possible causes. Dynamic Bayesian Networks (DBNs) are applied to address time factors and to model the dynamic changes of managed entities and the dependencies between them. Furthermore, prediction capabilities are investigated by means of the backward inference techniques. A simulation program is implemented to measure the presented backward inference and prediction strategies. Application issues are investigated for probabilistic fault management in distributed systems.

Gutachter
Prof. Dr.-Ing. habil. Herwig Unger
Prof. Dr.-Ing. Bernd Krämer, Fernuniversität in Hagen

FernUniversität in Hagen, Fakultät für Mathematik und Informatik, Lehrgebiet Datenverarbeitungstechnik, 58084 Hagen, Tel.: +49 2331 987-371, E-Mail: dvt-webmaster@fernuni-hagen.de