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

Bashar, Abul, Parr, Gerard, McClean, Sally, Scotney, Bryan and Nauck, Detlef (2010) Learning-based call admission control framework for QoS management in heterogeneous networks. Communications in Computer and Information Science, 88 CCIS (PART 2). pp. 99-111.

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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:	Article
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Smart Emerging Technologies (former - to 2025) Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory (former - to 2025) Faculty of Science > Research Groups > Data Science and AI
Depositing User:	Pure Connector
Date Deposited:	24 Sep 2016 00:34
Last Modified:	28 Mar 2025 07:41
URI:	https://ueaeprints.uea.ac.uk/id/eprint/60108
DOI:	10.1007/978-3-642-14306-9_11

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