Research Article
An Intelligent Active Queue Management Technique for congestion control
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 41 - Issue 16 |
| Published: March 2012 |
| Authors: G. Maria Priscilla, C. P. Sumathi |
10.5120/5625-7934
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G. Maria Priscilla, C. P. Sumathi . An Intelligent Active Queue Management Technique for congestion control. International Journal of Computer Applications. 41, 16 (March 2012), 25-28. DOI=10.5120/5625-7934
@article{ 10.5120/5625-7934,
author = { G. Maria Priscilla,C. P. Sumathi },
title = { An Intelligent Active Queue Management Technique for congestion control },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 41 },
number = { 16 },
pages = { 25-28 },
doi = { 10.5120/5625-7934 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A G. Maria Priscilla
%A C. P. Sumathi
%T An Intelligent Active Queue Management Technique for congestion control%T
%J International Journal of Computer Applications
%V 41
%N 16
%P 25-28
%R 10.5120/5625-7934
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Congestion an major problem in today's internet traffic had solution with TCP/IP congestion control mechanism. The active queue management (AQM) schemes stabilized the queue oscillations. Earlier RED AQM technique maintained the queue stability in which parameter setting was difficult. Hence a intelligent technique to stabilize the queue in the rapid growing traffic in internet was required. This paper proposes new unsupervised artificial neural network architecture with competitive learning mechanism. Learning vector quantization (LVQ) stabilizes the queue and reduces the queue oscillation. The results are compared with the Kohonen RED (KRED) and Modified Kohonen RED (MKRED) and prove that the proposed LVQ architecture stabilizes queue and maintain the queue delay.
References
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