A representative validation of a neural 3G admission control through rules extraction

Authors:
Anna Izabel J. Tastes Ribeiro;Luis E. Zárate;Fatima de L. P. Duarte Figueiredo
Affiliations:
Institute of Informatic, Pontifical Catholic University, Minas Gerais, Belo Horizonte, Brazil;Institute of Informatic, Pontifical Catholic University, Minas Gerais, Belo Horizonte, Brazil;Institute of Informatic, Pontifical Catholic University, Minas Gerais, Belo Horizonte, Brazil
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

Citing 4
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An Artificial Neural Network Approach for Mechanisms of Call Admission Control in UMTS 3G Networks

HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems

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Abstract

The proposal of new mechanisms and systems of call admission control has as objective the ensuring quality of service (QoS) for mobile networks. These mechanisms are evaluated through simulators, presenting some computational limitations. Recently, CAC-RD (Call Admission Control based on Reservation and Diagnosis) has been proposed as a new mechanism to simulate 3G UMTS networks, but a computational resources limitation was found. As example, to simulate 600 s of traffic with a limit of 1100 users, the simulation spent approximately 19 hours. This prevents a more real simulation in the presence of greater number of users. Recently, to surmount these limitations, the authors have presented CACRDNN (CAC-RD Neural Network), a new approach based on neural networks to represent quantitatively the CAC-RD, but it was verified that the new representation fails when qualitative aspects are evaluated. In this paper, the qualitative analysis of the mathematical representation of CAC-RDNN is evaluated. Results showed that CAC-RDNN reflects CAC-RD modules behavior in both quantitative and qualitative aspects, being able to simulate real networks.