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Next Generation Data Technologies for Collective Computational Intelligence pp 473–502Cite as

Next Generation Service Delivery Network as Enabler of Applicable Intelligence in Decision and Management Support Systems

Migration Strategies, Planning Methodologies, Architectural Design Principles

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 352))

Abstract

The crucial challenge that the communication industry has been wrestling with is the issue of how its underlying technologies should evolve and be used to help service providers remain competitive for many years in an environment marked by increased rivalry and deregulation. The Next Generation Network (NGN), with its decomposed architecture, can take full advantage of sophisticated technologies both to offer new services that will increase service providers’ revenues and reduce their operating costs. A strategy for evolving smoothly from modern networks to this new network structure is essential in order to minimize the required investment during the transition phase. However, any steps that are taken during this transition must make it easier for the networks to evolve ultimately to the NGN. Thus, the migration strategy proposed and explored in this chapter enables the development of a capable concept of how the structuring of networks must be changed, and in doing so takes into consideration the business needs of diverse service providers and network operators.

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Author information

Authors and Affiliations

  1. Department of eBusiness, School of Business, Economics and Statistics, University of Vienna, Vienna, Austria

    N. Kryvinska & C. Strauss

  2. Department of Computer Sciences, University of Salzburg, Salzburg, Austria

    P. Zinterhof

Authors
  1. N. Kryvinska
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  2. C. Strauss
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  3. P. Zinterhof
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Editor information

Editors and Affiliations

  1. School of Computing & Maths, University of Derby, DE22 1GB, Derby, United Kingdom (UK)

    Nik Bessis

  2. Dept de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Barcelona, Spain

    Fatos Xhafa

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© 2011 Springer-Verlag Berlin Heidelberg

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Kryvinska, N., Strauss, C., Zinterhof, P. (2011). Next Generation Service Delivery Network as Enabler of Applicable Intelligence in Decision and Management Support Systems. In: Bessis, N., Xhafa, F. (eds) Next Generation Data Technologies for Collective Computational Intelligence. Studies in Computational Intelligence, vol 352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20344-2_18

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  • DOI: https://doi.org/10.1007/978-3-642-20344-2_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20343-5

  • Online ISBN: 978-3-642-20344-2

  • eBook Packages: EngineeringEngineering (R0)

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