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Learning-Based Call Admission Control Framework for QoS Management in Heterogeneous Networks

  • Abul Bashar
  • Gerard Parr
  • Sally McClean
  • Bryan Scotney
  • Detlef Nauck
Part of the Communications in Computer and Information Science book series (CCIS, volume 88)

Abstract

This paper presents a novel framework for Quality of Service (QoS) management based on the supervised learning approach, Bayesian Belief Networks (BBNs). Apart from proposing the conceptual framework, it provides solution to the problem of Call Admission Control (CAC) in the converged IP-based Next Generation Network (NGN). A detailed description of the modelling procedure and the mathematical underpinning is presented to demonstrate the applicability of our approach. Finally, the theoretical claims have been substantiated through simulations and comparative results are provided as a proof of concept.

Keywords

Quality of Service (QoS) Call Admission Control (CAC) Bayesian Belief Networks (BBNs) Next Generation Network (NGN) 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Abul Bashar
    • 1
  • Gerard Parr
    • 1
  • Sally McClean
    • 1
  • Bryan Scotney
    • 1
  • Detlef Nauck
    • 2
  1. 1.School of Computing and EngineeringUniversity of UlsterColeraineUK
  2. 2.Research and Technology, British Telecom, Adastral ParkIpswichUK

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