TY - JOUR
T1 - Learning-based call admission control framework for QoS management in heterogeneous networks
AU - Bashar, Abul
AU - Parr, Gerard
AU - McClean, Sally
AU - Scotney, Bryan
AU - Nauck, Detlef
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
U2 - 10.1007/978-3-642-14306-9_11
DO - 10.1007/978-3-642-14306-9_11
M3 - Article
VL - 88 CCIS
SP - 99
EP - 111
JO - Communications in Computer and Information Science
JF - Communications in Computer and Information Science
IS - PART 2
ER -