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Assessing System Availability Using an Enterprise Architecture Analysis Approach

  • Jakob Raderius
  • Per Närman
  • Mathias Ekstedt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5472)

Abstract

During the last decade, a model based technique known as enterprise architecture has grown into an established approach for management of information systems in organizations. The use of enterprise architecture primarily promotes good decision-making and communication between business and IT stakeholders. This paper visualizes a scenario where enterprise architecture models are utilized to evaluate the availability of an information system. The problem is approached by creating models based on metamodels tailored to the domain of enterprise architecture analysis. As the instantiated models are fed with data particular to the information system, one can deduce how the organization needs to act in order to improve the system´s availability.

Keywords

Enterprise architecture architecture analysis Bayesian networks decision graphs availability 

References

  1. 1.
    Minoli, D.: Enterprise Architecture A to Z. s.l.: Auerbach (2008)Google Scholar
  2. 2.
    Zachman, J.A.: Concepts of the Framework for Enterprise Architecture (1992)Google Scholar
  3. 3.
    The Open Group Architecture Framework. TOGAF 8 Enterprise Edition. The Open Group, http://www.opengroup.org/togaf/
  4. 4.
    Johnson, P., et al.: Enterprise Architecture Analysis with Extended Influence Diagrams. Information System Frontiers, vol. 9. Springer, Netherlands (2007)Google Scholar
  5. 5.
    Jensen, F.: Bayesian Networks and Decision Graphs. Springer, New York (2001)CrossRefzbMATHGoogle Scholar
  6. 6.
    ISO/IEC. 9126-1 Software Engineering - Product Quality - Quality Model (2001)Google Scholar
  7. 7.
    Närman, P., Johnson, P., Nordström, L.: Enterprise Architecture: A Framework Supporting System Quality Analysis. In: Proceedings of the 11th International EDOC Conference (2007)Google Scholar
  8. 8.
    Hawkins, M., Piedad, F.: High Availability: Design,Techniques and Processes. Prentice Hall, Upper Saddle River (2001)Google Scholar
  9. 9.
    Nielsen, J.: Usability Engineering. Academic Press, San Diego (1993)zbMATHGoogle Scholar
  10. 10.
    Smith, C.U., Williams, L.G.: Performance Solutions: A Practical Guide to Creating Responsive, Scalable Software. Pearson Education, Indianapolis (2001)Google Scholar
  11. 11.
    IEEE. IEEE Standard Glossary of Software Engineering Terminology (1990)Google Scholar
  12. 12.
    Redman, T.: Data Quality for the Information Age. Artech House, Norwood (1996)Google Scholar
  13. 13.
    Stoneburner, G.: Underlying Technical Models for Information Technology Security. National Institute of Standards and Technology, Gaithersburg (2001)CrossRefGoogle Scholar
  14. 14.
    ISO/IEC. 9126-2 Technical Report - Software Engineering – Product Quality - Part 2: External Metrics (2003)Google Scholar
  15. 15.
    Sommeville, I., Sawyer, P.: Requirements Engineering. Wiley, Chichester (2004)Google Scholar
  16. 16.
    Johnson, P., Ekstedt, M.: Enterprise Architecture - Models and Analyses for Information Systems Decision Making. s.l.: Studentlitteratur (2007) ISBN 9789144027524Google Scholar
  17. 17.
    Addy, R.: Effective Service Management - To ITIL and Beyond. s.l. Springer, Heidelberg (2007)Google Scholar
  18. 18.
    Shachter, R.: Evaluating influence diagrams. Operations Research, vol. 34(6). Institute for Operations Research and the Management Sciences, Hanover Maryland (1986)Google Scholar
  19. 19.
    Howard, R.A., Matheson, J.E.: Decision Analysis. Influence Diagrams, vol. 2(3). Institute for Operations Research and the Management Sciences, Hanover Maryland (2005)Google Scholar
  20. 20.
    Neapolitan, R.: Learning Bayesian Networks. Prentice-Hall, Inc., Upper Saddle River (2003)Google Scholar
  21. 21.
    GeNIe & SMILE. GeNIe Website (2008), http://genie.sis.pitt.edu
  22. 22.
    Raderius, J.: Assessing the quality of service of an enterprise data warehouse. ICS, KTH, Stockholm (2008)Google Scholar
  23. 23.
    Trivedi, K., et al.: Achieving and Assuring High Availability. LNCS. Springer, Heidelberg (2008)Google Scholar
  24. 24.
    Sahner, R.A., Trivedi, K.S., Puliafito, A.: Performance and Reliability Analysis of Computer Systems. Kluwer Academic Press, Dordrecht (1996)CrossRefzbMATHGoogle Scholar
  25. 25.
    Trivedi, K.S.: Probability & Statistics with Reliability, Queueing and Computer Science Applications, 2nd edn. John Wiley, New York (2001)Google Scholar
  26. 26.
    Zhou, L., Held, M., Sennhauser, U.: Connection availability analysis of span-restorable mesh networks. Springer Science, Heidelberg (2006)Google Scholar
  27. 27.
    Grønbæk, J., et al.: Client-Centric Performance Analysis of a High-Availability Cluster (2007)Google Scholar
  28. 28.
    Johnson, P., et al.: A Tool for Enterprise Architecture Analysis. In: Proceedings of the 11th International EDOC Conference (2007) Google Scholar
  29. 29.
    Gammelgård, et al.: Architecture Scenario Analysis – Estimating the Credibility of the Results. In: Proceedings of the Seventeenth Annual International Symposium of The International Council on Systems Engineering (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jakob Raderius
    • 1
  • Per Närman
    • 1
  • Mathias Ekstedt
    • 1
  1. 1.Department of Industrial Information and Control SystemsRoyal Institute of Technology (KTH)StockholmSweden

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