The week's pick
Reseach Article
An Intelligent Active Queue Management Technique for congestion control
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 41 - Number 16 |
| Year of Publication: 2012 |
| Authors: G. Maria Priscilla, C. P. Sumathi |
10.5120/5625-7934
|
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
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
- S. Floyd and V. Jacobson, "Random early detection gateways for congestion avoidance," IEEE/ACM Trans. Networking, vol. 1, no. 4, pp. 397–413, Aug. 1993.
- Yang Richard Yang and Simon S. Lam "General AIMD Congestion Control "Proceedings of ICNP 2000, Osaka , Japan , November 2000.
- Wu-chang Feng ,"Improving internet congestion control and queue management algorithms ".
- . Rahul Verma, Aravind Iyer and Abhay Karandikar "Active Queue Management using Adaptive RED" Journal of communications and networks july 15 2002
- Emmanuel Lochin and BrunoTalavera "Managing network congestion with a Kohonen-based RED queue" ICC 2008 proceedings
- G. Maria Priscilla and Antony Selvadoss Thanamani,"managing network congestion with a modified Kohonen based RED queue", International Journal of Engineering Science and Technology Vol. 2(11), 2010, 6747-6752
- T. Kohonen. Learning vector quantization. In: M. A. Arbib, editor, The Handbook of Brain Theory and Neural Networks. , pages 537–540. MIT Press, Cambridge, MA, 1995.
- Kohonen, T. , The Self-Organizing Map, Proceedings of the IEEE, Vol. 78, No. 9,1990, pp. 1464-1480.
- Arijit Ganguly and Pasi Lassila "A study of TCP-RED congestion control using ns2"
- Dina Goren-Bar, Tsvi Kuflik, Dror Lev "supervised learning for automatic classification of documents using self- organizing maps"
- Vincent Cheung and Kevin Cannons "An introduction to neural networks "
- Chrysostomos Koutsimanis and Pan Gan Park " Active Queue Management – A router based control mechanism "
Index Terms
Keywords