Traffic prediction and dynamic bandwidth allocation over ATM: a neural network approach

Authors:
W Melody Moh;Min-Jia Chen;Nui-Ming Chu;Cherng-Der Liao
Affiliations:
Department of Mathematics and Computer Science, San Jose State University, San Jose, CA 95192-0103, USA;Department of Mathematics and Computer Science, San Jose State University, San Jose, CA 95192-0103, USA;Department of Mathematics and Computer Science, San Jose State University, San Jose, CA 95192-0103, USA;Department of Mathematics and Computer Science, San Jose State University, San Jose, CA 95192-0103, USA
Venue:
Computer Communications
Year:
1995

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Abstract

ATM (Asynchronous Transfer Mode) has been recommended as the transport vehicle for Broadband Integrated Service Digital Networks (BISDN). The ATM technology offers a great flexibility of transmission bandwidth allocation to accommodate diverse demands of multimedia connections, which include data, voice, video, graphics and images. One major application in ATM networks is to provide real-time, low-loss and minimum-delay transmission of variable bit rate (VBR) traffic which is highly bursty, non-stationary and correlated. In this work we adopt neural network methodology to predict VBR traffic represented by a continuous autoregressive (AR) Markov model. We have found that a simple 1-5-1 backpropagation neural network can accurately predict the VBR traffic. Based on prediction results obtained from neural networks, we propose a dynamic bandwidth allocation scheme for ATM. The proposed scheme is simulated under various traffic loads and buffer sizes. Its performance in terms of cell loss, cell delay and link utilization is examined and compared with two other bandwidth allocation schemes: the static average bandwidth allocation scheme, and the optimal (ideal) bandwidth allocation scheme. Experiments show that for most of the time, performance of the proposed dynamic bandwidth allocation is much better than that of the static average bandwidth allocation, and in many cases it is very close to that of the ideal bandwidth allocation.