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Neural Networks for QoS Network Management

  • Rafael del-Hoyo-Alonso
  • Pilar Fernández-de-Alarcón
  • Juan-José Navamuel-Castillo
  • Nicolás J. Medrano-Marqués
  • Bonifacio Martin-del-Brio
  • Julián Fernández-Navajas
  • David Abadía-Gallego
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4507)

Abstract

In this paper we explore the interest of computational intelligence tools in the management of heterogeneous communication networks, specifically to predict congestion, failures and other anomalies in the network that may eventually lead to degradation of the quality of offered services. We show two different applications based on neural and neurofuzzy systems for Quality of Service (QoS) management in next generation networks for V2oIP services. The two examples explained in this paper attempt to predict the communication network resources for new incoming calls, and visualizing by means of self-organizing maps the QoS of a communication network.

Keywords

Intelligent network Call Access Control IP Networks QoS Neural Networks Neuro-Fuzzy Systems EFUNN Self-Organizing Maps 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Rafael del-Hoyo-Alonso
    • 1
  • Pilar Fernández-de-Alarcón
    • 1
  • Juan-José Navamuel-Castillo
    • 1
  • Nicolás J. Medrano-Marqués
    • 2
  • Bonifacio Martin-del-Brio
    • 2
  • Julián Fernández-Navajas
    • 2
  • David Abadía-Gallego
    • 1
  1. 1.Instituto Tecnológico de Aragón, C/ María Luna nº6, 50018 ZaragozaSpain
  2. 2.Departamento de Electrónica y Comunicaciones, University of Zaragoza, C/ María Luna 1, 50018 ZaragozaSpain

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