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Learning-based Call Admission Control Framework for QoS Management in Heterogeneous Network

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Bashar, Abul, Parr, Gerard, McClean, Sally, Bryan, Scotney and Nauck, Detlef (2010) Learning-based Call Admission Control Framework for QoS Management in Heterogeneous Network. In: Networked Digital Technologies. Springer-Verlag Berlin Heidelberg, pp. 99-111. ISBN 978-3-642-14305-2 (Print) 978-3-642-14306-9 (Online) [Book section]

Full text not available from this repository.

DOI: 10.1007/978-3-642-14306-9_11

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.

Item Type:Book section
Keywords:Quality of Service (QoS) - Call Admission Control (CAC) - Bayesian Belief Networks (BBNs) - Next Generation Network (NGN)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:21990
Deposited By:Dr Cathryn Peoples
Deposited On:08 May 2012 16:15
Last Modified:08 May 2012 16:15

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