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.
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Salfner, F., Hoffmann, G., Malek, M. (2005). Prediction-Based Software Availability Enhancement. In: Babaoglu, O., et al. Self-star Properties in Complex Information Systems. SELF-STAR 2004. Lecture Notes in Computer Science, vol 3460. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428589_10
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DOI: https://doi.org/10.1007/11428589_10
Publisher Name: Springer, Berlin, Heidelberg
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