research-article

AD-RED: : A new variant of random early detection AQM algorithm

Author: Samuel O. HassanAuthors Info & Claims

Journal of High Speed Networks, Volume 30, Issue 1

Pages 53 - 67

https://doi.org/10.3233/JHS-222055

Published: 01 January 2024 Publication History

Abstract

Intensive continuing research has been noticed among scholars in the literature with a particular appreciable interest in developing new enhanced variants for the long-standing Random Early Detection (RED) algorithm. Contemporary trends shows that researchers continue to follow a research line thereby exchanging the linear curve needed in RED with nonlinear curves. Several reports have shown that RED’s sole linear function is insufficiently powered for managing rising degrees of traffic congestion in the network. In this paper, Amended Dropping – Random Early Detection (AD-RED), a revised version of RED is presented. AD-RED algorithm consists in combining two nonlinear packet dropping functions: quadratic plus exponential. What’s more, results from ns-3 simulator shows that AD-RED reasonably stabilized and minified the (average) queue size; and obtained a whittled down end-to-end delay when compared with RED itself and another variant of RED. Hence, AD-RED is offered as a fully sufficient replacement for RED’s algorithm implementation in routers.

References

[1]

A. Adamu, Y. Surajo and M.T. Jafar, SARED: Self-adaptive active queue management scheme for improving quality of service in network systems, Journal of Computer Science 22(2) (2021), 253–267.

[2]

A. Adamu, V. Shorgin, S. Melnikov and Y. Gaidamaka, Flexible random early detection algorithm for queue management in routers, in: International Conference on Distributed Computer and Communication Networks, Springer, Cham, 2020, pp. 196–208.

[3]

L. Pei, F. Wu and S. Wang, Periodic, quasi-periodic and chaotic oscillations in two heterogeneous AIMD/RED network congestion models with state-dependent round-trip delays, International Journal of Bifurcation and Chaos 31(6) (2021), 2150124.

[4]

A. Giménez, M.A. Murcia, J.M. Amigó, O. Martínez-Bonastre and J. Valero, New RED-type TCP-AQM algorithms based on beta distribution drop functions, 2022, [cs.NI].

[5]

S. Sunassee, A. Mungur, S. Armoogum and S. Pudaruth, A comprehensive review on congestion control techniques in networking, in: Proceedings of the 5th International Conference on Computing Methodologies and Communication (ICCMC), 2021, pp. 305–312.

[6]

N. Kaur and R. Singhai, Congestion control scheme using network coding with local route assistance in mobile adhoc network, International Journal of Computer Applications in Technology 60(3) (2019), 242–253.

Digital Library

[7]

G. Thiruchelvi and J. Raja, A survey on active queue management mechanisms, International Journal of Computer Science and Network Security 8(12) (2008), 130–145.

[8]

H. Abdel-Jaber, A. Shehab, M. Barakat and M. Rashad, Igred: An improved gentle random early detection method for management of congested networks, Journal of Interconnection Networks 19(2) (2019), 1950004.

[9]

H. Abdel-Jaber, An exponential active queue management method based on random early detection, Journal of Computer Networks and Communications 2020 (2020), 1–11.

Digital Library

[10]

A.A. Abu-Shareha, Controlling delay at the router buffer using modified random early detection, International Journal of Computer Networks and Communications (IJCNC) 11(6) (2019), 63–75.

[11]

X. Dang, L. Ma and X. Liu, CCAIB: Congestion control based on adaptive integral backstepping for wireless multi-router network, Sensors 2022(22) (2022), 1–15.

[12]

A. Ahmed and N. Nasrelden, New congestion control algorithm to improve computer networks performance, in: Proceedings of the 2018 International Conference on Innovative Trends in Computer Engineering, 2018, pp. 87–93.

[13]

L. Chen, X. Wang and Z. Han, Controlling chaos in Internet congestion control model, Chaos, Solitons and Fractals 21(1) (2004), 81–91.

[14]

S. Ryu, C. Rump and C. Qiao, Advances in Internet Congestion Control, IEEE Communications Surveys and Tutorials 5(1) (2003), 28–39.

Digital Library

[15]

S. Patel and Karmeshu, A new modified dropping for congested networks, Wireless Personal Communications 104(1) (2019), 37–55.

Digital Library

[16]

B. Braden, D. Clark, J. Crowcroft, B. Davie, S. Deering, D. Estrin, S. Floyd, V. Jacobson, G. Minshall, C. Patridge, L. Peterson, K. Ramakrishnan, S. Shenker, J. Wroclawski and L. Zhang, Recommendations on Queue Management and Congestion Avoidance in the Internet, RFC 2309, 1998.

[17]

M. Barczyk and A. Chydzinski, AQM based on the queue: A real-network study, PLos ONE 17(2) (2022), 1–22.

[18]

S. Kar, B. Alt, H. Koeppl and A. Rizk, PAQMAN: A principled approach to active queue management, 2022, [cs.PF].

[19]

M.Q. Sulttan, M.H. Jaber and S.W. Shneen, Proportional-integral genetic algorithm controller for stability of TCP network, International Journal of Electrical and Computer Engineering 10(6) (2020), 6225–6232.

[20]

F. Baker and G. Fairhurst, IETF recommendations regarding active queue management, RFC 7567 (2015).

Digital Library

[21]

C. Brandauer, G. Iannaccone, C. Diot, T. Ziegler, S. Fdida and M. May, Comparison of tail drop and active queue management performance for bulk-data and web-like Internet traffic, in: Proceedings of the Sixth IEEE Symposium on Computers and Communications, 2001, pp. 122–129.

[22]

S. Floyd and V. Jacobson, Random early gateway for congestion avoidance, IEEE/ACM Transactions on Networking 1(4) (1993), 397–413.

Digital Library

[23]

K. Kato, H. Kato, H. Asahara, D. Ito and T. Kousaka, Effects on random early detection of the packet drop probability function with an adjustable nonlinearity, Nonlinear Theory and Its Applications (NOLTA) 14(2) (2023), 193–206.

[24]

S.T.A. Jafri, I. Ahmed and S. Ali, Queue-buffer optimization based on aggressive random early detection in massive NB-IoT MANET for 5G applications, Electronics 11(18) (2022), 1–18.

[25]

K. Zhou, K.L. Yeung and V.O.K. Li, Nonlinear RED: A simple yet efficient active queue management scheme, Journal of Computer Networks 50(18) (2006), 3784–3794.

Digital Library

[26]

S. Floyd, Recommendation on using the “gentle” variant of RED, 2000, Available online at https://icir.org/floyd/red/gentle.html.

[27]

Y. Zhang, J. Ma, Y. Wang and C. Xu, MRED: An improved nonlinear RED algorithm, in: Proceedings of the 2011 International Conference on Computer and Automation Engineering (ICCAE 2011), Vol. 44, 2012, pp. 6–11.

[28]

S.O. Hassan and A. Rufai, Modified Dropping – Random Early Detection (MD-RED): A modified algorithm for controlling network congestion, International Journal of Information Technology 15(3) (2023), 1499–1508.

[29]

H. Abdel-Jaber, F. Thabtah and M. Woodward, Modeling discrete-time analytical models based on random early detection: Exponential and linear, International Journal of Modeling, Simulation, and Scientific Computing 6(3) (2015), 155028.

[30]

D. Kumhar, A. Kumar and A. Kewat, QRED: An enhancement approach for congestion control in network communications, International Journal of Technology 13 (2021), 221–227.

[31]

C. Suwannapong and C. Khunboa, Congestion control in CoAP observe group communication, Sensors 19(3433) (2019), 1–14.

[32]

B. Zheng and M. Atiquzzaman, DSRED: A new queue management scheme for the next generation Internet, IEICE Trans. Commun. E E89 (2006), 764–774.

[33]

J. Domańska, D.R. Augustyn and A. Domański, The choice of optimal 3-rd order polynomial packet dropping function for NLRED in the presence of self-similar traffic, Bulletin of the Polish Academy of Sciences Technical Sciences 60(4) (2012), 779–786.

[34]

A.K. Paul, H. Kawakami, A. Tachibana and T. Hasegawa, An aqm based congestion control for enb rlc in 4g/lte network, in: Proceedings of the 2016 IEEE Canandian Conference on Electrical and Computer Engineering (CCECE), 2016, pp. 1–5.

[35]

S.O. Hassan, V.O. Nwaocha, A.U. Rufai, T.J. Odule, T.A. Enem, L.A. Ogundele and S.A. Usman, Random early detection-quadratic linear: An enhanced active queue management algorithm, Bulletin of Electrical Engineering and Informatics 11(4) (2022), 2262–2272.

[36]

C. Suwannapong and C. Khunboa, EnCoCo-RED: Enhanced congestion control mechanism for CoAP observe group communication, Journal of Ad Hoc Networks 112 (2021), 1–10.

[37]

A.K. Paul, H. Kawakami, A. Tachibana and T. Hasegawa, Effect of AQM-based RLC buffer management on the eNB scheduling algorithm in LTE network, Technology 5(59) (2017), 1–7.

[38]

S.O. Hassan, A.U. Rufai, C. Ajaegbu and F. Ayankoya, DL-RED: A RED-based algorithm for routers, International Journal of Computer Applications in Technology 70(3/4) (2022), 244–253.

[39]

M. Baklizi, H. Abdel-Jaber, S. Ramadass, N. Abdullah and M. Anbar, Performance assessment of AGRED, RED and GRED congestion control algorithms, Information Technology Journal 11(2) (2012), 255–261.

[40]

S.O. Hassan, RED-LE: A revised algorithm for active queue management, Journal of Telecommunications and Information Technology 2 (2022), 91–97.

[41]

C.-W. Feng, L.-F. Huang, C. Xu and Y.-C. Chang, Congestion control scheme performance analysis based on nonlinear RED, IEEE Systems Journal 11(4) (2017), 2247–2254.

[42]

Y. Bie, Z. Li, Z. Hu and J. Chen, Queue management algorithm for satellite network based on traffic prediction, IEEE Access 10 (2022), 54313–54324.

[43]

N. S. Foundation, The network simulator – ns3, 2006, https://www.nsnam.org, accessed: 2021-08-10.

[44]

N. Kuhn, P. Natarajan, N. Khademi and D. Ros, Characterization guidelines for Active Queue Management (AQM), RFC 7928 (2016).

Digital Library

Cited By

Zaryadov IMilovanova TSamouylov K(2024)Probability Characteristics of Queuing Systems with Two Different Threshold-Based Stochastic Drop MechanismsDistributed Computer and Communication Networks10.1007/978-3-031-80853-1_23(312-326)Online publication date: 23-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-80853-1_23

Index Terms

AD-RED: A new variant of random early detection AQM algorithm
1. General and reference
  1. Cross-computing tools and techniques
2. Networks

Index terms have been assigned to the content through auto-classification.

Recommendations

Efficient congestion avoidance mechanism
LCN '00: Proceedings of the 25th Annual IEEE Conference on Local Computer Networks

Increasing uncontrolled best-effort traffic deteriorates the ability of TCP to control congestion and is a source of high drop rates. This paper proposes an efficient congestion avoidance mechanism (ECAM) suitable for uncontrolled unicast and multicast ...
TCP tunnels: avoiding congestion collapse
LCN '00: Proceedings of the 25th Annual IEEE Conference on Local Computer Networks

This paper examines the attributes of TCP tunnels which are TCP circuits that carry IP packets and benefit from the congestion control mechanism of TCP/IP. The deployment of TCP tunnels reduces the many flows situation on the Internet to that of a few ...
Comparative performance analysis of TCP-based congestion control algorithms

Congestion control is a challenging problem for us. We tried to analyse the end-to-end congestion control algorithms, i.e., TCP Tahoe, TCP Reno, TCP Newreno, TCP Veno, etc. In the literature, TCP implements a window-based flow control mechanism which ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of High Speed Networks

Journal of High Speed Networks Volume 30, Issue 1

2024

142 pages

ISSN:0926-6801

Issue’s Table of Contents

© 2024 – IOS Press. All rights reserved.

Publisher

IOS Press

Netherlands

Publication History

Published: 01 January 2024

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Zaryadov IMilovanova TSamouylov K(2024)Probability Characteristics of Queuing Systems with Two Different Threshold-Based Stochastic Drop MechanismsDistributed Computer and Communication Networks10.1007/978-3-031-80853-1_23(312-326)Online publication date: 23-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-80853-1_23

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents