Hybrid histogram and neural based call admission control for VBR video traffic.

In this paper, we have proposed a hybrid Neural Network (NN) approach to estimate cell loss rate of Variable Bit Rate (VBR) Video traffic for Call Admission Control (CAC) purpose in ATM environment Existing CAC algorithms, which are mostly based on on-off model, do not appear to apply well to VBR vi...

Full description

Bibliographic Details
Main Authors: Khalil, Ibrahim, Mohd Ali, Borhanuddin
Format: Conference or Workshop Item
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/25643/
_version_ 1848845361866604544
author Khalil, Ibrahim
Mohd Ali, Borhanuddin
author_facet Khalil, Ibrahim
Mohd Ali, Borhanuddin
author_sort Khalil, Ibrahim
building UPM Institutional Repository
collection Online Access
description In this paper, we have proposed a hybrid Neural Network (NN) approach to estimate cell loss rate of Variable Bit Rate (VBR) Video traffic for Call Admission Control (CAC) purpose in ATM environment Existing CAC algorithms, which are mostly based on on-off model, do not appear to apply well to VBR video traffic. In reality, VBR video sources are not two-state on-off sources. Recently, a histogram-based model for video traffic behavior has been proposed which is able to overcome most of the deficiencies in conventional approaches and can handle VBR video traffic in various traffic situations. It, however, has some problems: unable to guarantee cell loss rates for short burst periods; overestimation of cell loss rates during call set up etc. We have, therefore, proposed a NN based hybrid approach, where NN is used to refine the evaluation result by applying the knowledge gained of the actual performance of the histogram scheme. We have shown how performance data derived from histogram based approach can be used as training data in the NN training scheme to produce even better results than the pure histogram based approach, while still retaining the merits of it.
first_indexed 2025-11-15T08:45:36Z
format Conference or Workshop Item
id upm-25643
institution Universiti Putra Malaysia
institution_category Local University
last_indexed 2025-11-15T08:45:36Z
recordtype eprints
repository_type Digital Repository
spelling upm-256432015-05-19T06:49:15Z http://psasir.upm.edu.my/id/eprint/25643/ Hybrid histogram and neural based call admission control for VBR video traffic. Khalil, Ibrahim Mohd Ali, Borhanuddin In this paper, we have proposed a hybrid Neural Network (NN) approach to estimate cell loss rate of Variable Bit Rate (VBR) Video traffic for Call Admission Control (CAC) purpose in ATM environment Existing CAC algorithms, which are mostly based on on-off model, do not appear to apply well to VBR video traffic. In reality, VBR video sources are not two-state on-off sources. Recently, a histogram-based model for video traffic behavior has been proposed which is able to overcome most of the deficiencies in conventional approaches and can handle VBR video traffic in various traffic situations. It, however, has some problems: unable to guarantee cell loss rates for short burst periods; overestimation of cell loss rates during call set up etc. We have, therefore, proposed a NN based hybrid approach, where NN is used to refine the evaluation result by applying the knowledge gained of the actual performance of the histogram scheme. We have shown how performance data derived from histogram based approach can be used as training data in the NN training scheme to produce even better results than the pure histogram based approach, while still retaining the merits of it. Conference or Workshop Item NonPeerReviewed Khalil, Ibrahim and Mohd Ali, Borhanuddin Hybrid histogram and neural based call admission control for VBR video traffic. In: International Conference on Artificial Neural Networks, 26 - 28 June 1995, Cambridge, UK. (pp. 421-426). Neural networks Asynchronous transfer mode Algorithms
spellingShingle Neural networks
Asynchronous transfer mode
Algorithms
Khalil, Ibrahim
Mohd Ali, Borhanuddin
Hybrid histogram and neural based call admission control for VBR video traffic.
title Hybrid histogram and neural based call admission control for VBR video traffic.
title_full Hybrid histogram and neural based call admission control for VBR video traffic.
title_fullStr Hybrid histogram and neural based call admission control for VBR video traffic.
title_full_unstemmed Hybrid histogram and neural based call admission control for VBR video traffic.
title_short Hybrid histogram and neural based call admission control for VBR video traffic.
title_sort hybrid histogram and neural based call admission control for vbr video traffic.
topic Neural networks
Asynchronous transfer mode
Algorithms
url http://psasir.upm.edu.my/id/eprint/25643/