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Prediction-Based Software Availability Enhancement

  • Felix Salfner
  • Günther Hoffmann
  • Miroslaw Malek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3460)

Abstract

We propose a new paradigm for software availability enhancement. We offer a two-step strategy: Failure prediction followed by maintenance actions with the objective of avoiding impending failures or minimizing the effort of their repair. For the first step we present two failure prediction methods: universal basis functions (UBF) and similar events prediction (SEP), which are based on probabilistic analysis. The potential of the presented methods is evaluated by a case-study where failures of a commercial telecommunication platform have been predicted. The second step includes existing maintenance methods fitting the proposed approach and a new recovery strategy called “adaptive recovery blocks”. Since system availability enhancement is the overall goal, equations to calculate availability of such a system are given as well.

Keywords

Preventive Maintenance Software Aging Acceptance Test System Availability Failure Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Felix Salfner
    • 1
  • Günther Hoffmann
    • 1
  • Miroslaw Malek
    • 1
  1. 1.Institut für InformatikHumboldt-Universität zu Berlin 

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