Learning-based call admission control framework for QoS management in heterogeneous networks

Abul Bashar, Gerard Parr, Sally McClean, Bryan Scotney, Detlef Nauck

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)99-111
Number of pages13
JournalCommunications in Computer and Information Science
Volume88 CCIS
Issue numberPART 2
Publication statusPublished - 2010

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