Call for Paper - November 2022 Edition
IJCA solicits original research papers for the November 2022 Edition. Last date of manuscript submission is October 20, 2022. Read More

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

Print
PDF
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.