A coupled fuzzy logic control for routers' queue management over TCP/AQM networks

Li, Zhi and Zhang, Zhongwei (2005) A coupled fuzzy logic control for routers' queue management over TCP/AQM networks. In: 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES 2005), 14-16 Sep 2005, Melbourne, Australia.

Abstract

Significant efforts in developing active queue management (AQM) in gateway routers in a TCP/IP network have been made since random early detection (RED) in 1993, and most of them are statistical based. Our approach is to capitalize on the understanding of the TCP dynamics to design an effective AQM scheme. In this paper, two FL-based AQM algorithms are proposed with the deployment of traffic load factor for early congestion notification. Extensive experimental simulations with a range of traffic load conditions have been done for the purpose of performance evaluation. The results show that the proposed two FLAQM algorithms outperform some well-known AQM schemes in terms of both user-centric measures and network-centric measures.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restrcited access to published verison due to publisher copyright policy.
Depositing User: epEditor USQ
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 11 Sep 2011 04:39
Last Modified: 02 Jul 2013 22:34
Uncontrolled Keywords: algorithms; fuzzy sets; information management; network protocols; queueing networks; routers; telecommunication traffic
Fields of Research (FOR2008): 10 Technology > 1005 Communications Technologies > 100503 Computer Communications Networks
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation
08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
URI: http://eprints.usq.edu.au/id/eprint/783

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