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Using Enterprise Architecture Models and Bayesian Belief Networks for Failure Impact Analysis

  • Oliver Holschke
  • Per Närman
  • Waldo Rocha Flores
  • Evelina Eriksson
  • Marten Schönherr
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5472)

Abstract

The increasing complexity of enterprise information systems makes it very difficult to prevent local failures from causing ripple effects with serious repercussions to other systems. This paper proposes the use of Enterprise Architecture models coupled with Bayesian Belief Networks to facilitate Failure Impact Analysis. By extending the Enterprise Architecture models with the Bayesian Belief Networks we are able to show not only the architectural components and their interconnections but also the causal influence the availabilities of the architectural elements have on each other. Furthermore, by using the Diagnosis algorithm implemented in the Bayesian Belief Network tool GeNIe, we are able to use the network as a Decision Support System and rank architectural components with their respect to criticality for the functioning of a business process. An example featuring a car rental agency demonstrates the approach.

Keywords

Enterprise Architecture Management Decision Support Systems SOA Bayesian Belief Nets Diagnosis Failure Impact Analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Oliver Holschke
    • 1
  • Per Närman
    • 2
  • Waldo Rocha Flores
    • 2
  • Evelina Eriksson
    • 2
  • Marten Schönherr
    • 3
  1. 1.Technische Universität Berlin, Fachgebiet Systemanalyse und EDV, FR 6-7BerlinGermany
  2. 2.Dpt. of Industrial Information and Control SystemsRoyal Institute of Technology (KTH)StockholmSweden
  3. 3.Deutsche Telekom LaboratoriesBerlinGermany

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