Optimal congestion bit setting in a flow control scheme using neural networks

James Aweya, Delfin Y. Montuno, Qi jun Zhang, Luis Orozco-Barbosa

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

In this paper, we describe a neural network-based technique for optimal congestion bit setting in a binary feedback flow control scheme for computer networks. This technique employs the sensitivity of the system performance to generate feedback from the network to the data sources. The optimal direction for rate adjustment at the source is based on a single bit feedback signal from the network which depends upon the sign of the sensitivity of the system performance index with respect to the network queue input rate. Simulation results are presented to show the performance of this gradient-based technique compared to the conventional queue-based approach for congestion detection.

Original languageBritish English
Pages2675-2682
Number of pages8
StatePublished - 1998
EventProceedings of the IEEE GLOBECOM 1998 - The Bridge to the Global Integration - Sydney, NSW, Aust
Duration: 8 Nov 199812 Nov 1998

Conference

ConferenceProceedings of the IEEE GLOBECOM 1998 - The Bridge to the Global Integration
CitySydney, NSW, Aust
Period8/11/9812/11/98

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