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Applying Fuzzy Logic Principles to Improve the Performance of the Random Early Detection Algorithm

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 122 - Number 17
Year of Publication: 2015
Authors:
A. I. A. Jabbar
Ahmed I. Al-ghannam
10.5120/21795-5172

A I A Jabbar and Ahmed I Al-ghannam. Article: Applying Fuzzy Logic Principles to Improve the Performance of the Random Early Detection Algorithm. International Journal of Computer Applications 122(17):27-31, July 2015. Full text available. BibTeX

@article{key:article,
	author = {A. I. A. Jabbar and Ahmed I. Al-ghannam},
	title = {Article: Applying Fuzzy Logic Principles to Improve the Performance of the Random Early Detection Algorithm},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {122},
	number = {17},
	pages = {27-31},
	month = {July},
	note = {Full text available}
}

Abstract

This paper proposes a Random early detection algorithm based on fuzzy logic Principles. The main target of using the fuzzy logic is to reduce the number of lost packets which are sent by a sender using RED algorithm in queue-buffer router of the network topology. The function of fuzzy logic is to dynamically tune the maximum drop probability (maxp) parameter of the RED algorithm. To realize this target, a two-input-single-output fuzzy logic is implemented. The inputs of the fuzzy logic are average queue size, the difference in average queue size. To estimate the performance of the FLRED: simple network topology with FTP is suggested. In this research, the opnet modeler 14. 5 has been used. The simulation results show that the FLRED algorithm is better than traditional RED algorithm as far as the number of lost packets is concerned.

References

  • H. ASHTIANI, H. Moradi and M. NIKPOUR . " Active Queue Management in TCP Networks Based on Fuzzy-Pid Controller" , Journal of Applied Computer Science & Mathematics,2012.
  • Minjuan Cheng and Xiaoming Ma, " Performance Evaluation of Queue Management Methods for Congestion Control" , Journal of Information & Computational Science , 2012.
  • Arash Dana and Ahmad Malekloo, "Performance comparison between Active and Passive Queue Management" IJCSI International Journal of Computer Science Issues,2010.
  • Jingjun Zhanga, Wenlong Xub and Liguo Wangb, " An Improved Adaptive Active Queue Management Algorithm Based on Nonlinear Smoothing", Sciverse science direct, 2011.
  • S. Floyd and V. Jacson, Random Early Detection gateways for congestion avoidance, IEEE/ACM Trans. on Networking, 1993.
  • S. N. Sivanandam, S. Sumathi and S. N. Deepa , "Introduction to Fuzzy Logic using MATLAB" , Springer-Verlag Berlin Heidelberg 2007.
  • OPNET Technologies, Inc. http://www. opnet. com
  • T. Álvarez, V. Álvarez and L. Nicolás, "Understanding congestion control algorithm in TCP using OPNET", 2nd International Conference on Education and New Learning Technologies, 2010.