Document Type

Conference Proceeding

Publisher

IEEE Press

Faculty

Computing, Health and Science

School

Engineering, Centre for Communications Engineering Research

RAS ID

6203

Comments

This article was originally published as: Ahmad, I. , Kamruzzaman, J., Habibi, D. , & Islam, F. (2008). An Intelligent Model To Control Preemption Rate Of Instantaneous Request Calls In Networks With Book-Ahead Reservation. Proceedings of Australasian Telecommunication Networks and Applications Conference. ATNAC 2008. (pp. 344-348). Adelaide Australia. IEEE Press. Original article available here

Abstract

Resource sharing between book-ahead (BA) and instantaneous request (IR) reservation often results in high preemption rate of on-going IR calls. High IR call preemption rate causes interruption to service continuity which is considered as detrimental in a QoS-enabled network. A number of call admission control models have been proposed in literature to reduce the preemption rate of on-going IR calls. Many of these models use a tuning parameter to achieve certain level of preemption rate. This paper presents an artificial neural network (ANN) model to dynamically control the preemption rate of on-going calls in a QoS-enabled network. The model maps network traffic parameters and desired level of preemption rate into appropriate tuning parameter. Once trained, this model can be used to automatically estimate the tuning parameter value necessary to achieve the desired level of preemption rate. Simulation results show that the preemption rate attained by the model closely matches with the target rate.

DOI

10.1109/ATNAC.2008.4783348

 
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Link to publisher version (DOI)

10.1109/ATNAC.2008.4783348