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A Modified Random Early Detection Algorithm: Fuzzy Logic Based Approach  

Yaghmaee Mohammad Hossein
Publication Information
Abstract
In this paper, a fuzzy logic implementation of the random early detection (RED) mechanism [1] is presented. The main objective of the proposed fuzzy controller is to reduce the loss probability of the RED mechanism without any change in channel utilization. Based on previous studies, it is clear that the performance of RED algorithm is extremely related to the traffic load as well as to its parameters setting. Using fuzzy logic capabilities, we try to dynamically tune the loss probability of the RED gateway. To achieve this goal, a two-input-single-output fuzzy controller is used. To achieve a low packet loss probability, the proposed fuzzy controller is responsible to control the $max_{p}$ parameter of the RED gateway. The inputs of the proposed fuzzy controller are 1) the difference between average queue size and a target point, and 2) the difference between the estimated value of incoming data rate and the target link capacity. To evaluate the performance of the proposed fuzzy mechanism, several trials with file transfer protocol (FTP) and burst traffic were performed. In this study, the ns-2 simulator [2] has been used to generate the experimental data. All simulation results indicate that the proposed fuzzy mechanism out performs remarkably both the traditional RED and Adaptive RED (ARED) mechanisms [3]-[5].
Keywords
Active queue management (AQM); congestion control; fuzzy logic control; random early detection (RED);
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1 V. Jacobson, 'Congestion avoidance and control,' in Proc. ACM SIGCOMM'98, Aug. 1998, pp. 314-329
2 B. Wydrowski and M. Zukerman, 'GREEN: An active queue management algorithm for a self managed Internet,' in Proc. IEEE ICC 2002, New York, vol. 4, 2002, pp. 2368-2372   DOI
3 A. Pitsillides and Y. A. Sekercioglu, 'Fuzzy logic control of cell loss in asynchronous transfer mode (ATM),' in Proc. Australian Telecommun. Network App. Conf., Clayton, Australia, Dec. 1994, pp. 249-254
4 C. Chrysostomou, A. Pitsillides, G. Hadjipollas, A. Sekercioglu, and M. Polycarpou, 'Fuzzy logic congestion control in TCP/IP best-effort networks,' in Proc. ICTTA 2004, Damascus, Syria, Apr. 2004, pp. 19-23
5 L. X. Wang, A Course in Fuzzy Systems and Control, NJ: Prentice-Hall, 1997
6 K. Nichols, V. Jacobson, and L. Zhang, 'A two-bit differentiated services architecture for the Internet,' IETF RFC 2638, July 1999
7 S. Athuraliya, V. H. Li, S. H. Low, and Q. Yin, 'REM: Active queue management,' IEEE Network, May/June 2001
8 M. H. Yaghmaee, M. Safavi, and M. B. Menhaj, 'An intelligent usage parameter controller based on dynamic rate leaky bucket for ATM networksm,' Elsevier Science J. Computer Networks, vol. 32, pp. 17-34, 2000   DOI   ScienceOn
9 M. H. Yaghmaee, M. Safavi, and M. B. Menhaj, 'A novel fuzzy traffic controller for ATM networks,' in Proc. IEEE ISPACS'98, Melbourn, Australia, 1998, pp. 199-203
10 J. Heinane and R. Guerin, 'A single rate three color marker,' IETF RFC 2697, Sept. 1999
11 S. Blake, M. Carlson, E. Davies, Z. Wang, and W. Weiss, 'An architecture for differentiated services,' IETF RFC 2475, 1998
12 W. Feng, D. D. Kandlur, D. Saha, and K. Shin, 'Adaptive packet marking for providing differentiated services in the Internet,' in Proc. Int. Conf. Network Protocols, Austin, TX, 1998, pp. 108-117   DOI
13 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   DOI   ScienceOn
14 B. Bensaou, S. T. C. Lam, H.-W. Chu, and D. H. K. Tsang, 'Estimation of the cell loss ratio in ATM networks with a fuzzy system and application to measurement-based call admission control,' IEEE/ACM Trans. Networking, vol. 5, no. 4, pp. 572-584, 1997   DOI   ScienceOn
15 T. D. Ndousse, 'Fuzzy neural control of voice cells in ATM networks,' IEEE J. Select. Areas Commun., vol. 12, no. 9, pp.1488-1494, 1994   DOI   ScienceOn
16 The Network Simulator-ns-2 homepage, available at http://www.isi.edu/nsnam/ns/
17 M. H. Yaghmaee, M. Safavi, and M. B. Menhaj, 'A fuzzy connection admission controller for ATM networks,' in Proc. IEEE ISPACS'99, Pucket, Thailand, 1999
18 M. H. Yaghmaee, M. Safavi, and M. B. Menhaj, 'An efficient fuzzy based traffic policer for ATM networks,' IEICE Trans. Commun., vol. E83-B, no.1, pp. 10-19, 2000
19 J. S. Turner, 'New direction in communication,' in Proc. Int. Zurich Seminar Digital Commun., Zurich, 1986
20 T. Ott, T. Lakshman, and L. Wong, 'SRED: Stabilized RED,' in Proc. IEEE INFOCOM'99, 1999
21 W. Feng, D. Kandlur, D. Saha, and K. Shin, 'BLUE: A new class of active queue management algorithms,' U. Michigan CSE-TR-387-99, Apr. 1999
22 M. May, J. Bolot, C. Diot, and B. Lyles, 'Reasons not to deploy RED,' in Proc. IWQoS'99, June 1999, pp. 260-262   DOI
23 R. Pan, V. Prabhakar, and K. Psounis, 'Choke: A stateless active queue management scheme for approximating fair bandwidth allocation,' in Proc. IEEE INFOCOM 2000, Tel Aviv, Israel, vol. 2, Mar. 2000, pp. 942-951
24 M. P. Fernandez, A. de C. P. Pedroza, and J. F. de Rezende, 'Optimizing fuzzy controllers with genetic algorithms for QoS improvement,' in Proc. ITS 2002, Natal, Brazil, 2002
25 W. Feng, D. Kandlur, D. Saha, and K. Shin, 'Techniques for eliminating packet loss in congested TCP/IP network,' U. Michigan CSE-TR-349-97, Nov. 1997
26 R.-G. Cheng and C.-J. Chang, 'Design of a fuzzy traffic controller for ATM networks,' IEEE Trans. Networking, vol. 4, pp. 460-469, 1996   DOI   ScienceOn
27 C. Douligeris and G. Develekos, 'A fuzzy logic approach to congestion control in ATM networks,' in Proc. IEEE ICC'95, Seattle, WA, vol. 3, June 1995, pp. 1969-1973   DOI
28 W. Feng, D. Kandlur, D. Saha, and K. Shin, 'A self configuring RED gareway,' in Proc. IEEE INFOCOM'99, Mar. 1999
29 M. H. Yaghmaee, M. Safavi, and M. B. Menhaj, 'A high performance fuzzy traffic controller for ATM networks,' in Proc. IEEE ATM Workshop'99, Kochi, Japan, 1999, pp. 379-384   DOI
30 W. Fang, N. Seddigh, and B. Nandy, 'A time sliding window three color marker (TSWTCM),' IETF RFC 2859, June 2000
31 M. H. Yaghmaee, M. Safavi, and M. B. Menhaj, 'A novel FLC based approach for ATM traffic control,' Elsevier Science J. Computer Networks, vol. 36, no. 5/6, pp. 643-658, 2001   DOI   ScienceOn
32 M. P. Fernandez, A. de C. P. Pedroza, and J. F. de Rezende, 'QoS provisioning across a DiffServ domain using policy-based management,' in Proc. GLOBECOM 2001, San Antonio, USA, Nov. 2001
33 T. Li and Y. Rekhter, 'A provider architecture for differentiated services and traffic engineering (PASTE),' IETF RFC 2430, Oct. 1998
34 S. Ghosh, Q. Razouqi, H. J. Schumacher, and A. Celmins, 'A survey of recent advances in fuzzy logic in telecommunications networks and new challenges,' IEEE Trans. Fuzzy Syst., vol. 6, no. 3, pp. 443-447, 1998   DOI   ScienceOn
35 A. R. Bonde and S. Ghosh, 'A comparative study of fuzzy versus fixed threshold for robust queue management in cell-switching networks,' IEEE/ACM Trans. Networking, vol. 2, no. 4, pp. 337-344, 1994   DOI   ScienceOn
36 V. Catania, G. Ficili, S. Palazzo, and D. Panno, 'A comparative analysis of fuzzy versus conventional policing mechanism for ATM networks,' IEEE/ACM Trans. Networking, vol. 4, pp.449-459, 1996   DOI   ScienceOn
37 S. Floyd, R. Gummadi, and S. Shenker, 'Adaptive RED: An algorithm for increasing the robustness of RED,' Technical Report, 2001
38 C. Chrysostomoul, A. Pitsillides, L. Rossides, M. Polycarpou, and A. Sekercioglu, 'Congestion control in differentiated services networks using fuzzy-RED,' IFAC J. Control Eng. Practice, vol. 11, no. 10, pp. 1153-1170, 2003   DOI   ScienceOn