NN-RED: an AQM mechanism based on neural networks
Abstract
A novel active queue management (AQM) method is proposed. This method, named NN-RED, is based on the use of a neural network for early congestion prediction. By simulations, it is demonstrated that the performance of the proposed approach is better than the random early detection (RED) method that is currently known as one of the best AQM methods in solving congestion problems.
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NN-RED outperforms RED and Drop-tail in terms of queuing delay, dropped packets, and queue stability.
“Basic simulations exhibit that NN-RED outperforms RED and Drop-tail in terms of queuing delay, dropped packets, and queue stability.”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [179]
These AQM schemes apply different supervised techniques for TSF and reinforcement-based methods for deducing the increment in the packet drop probability.
“these AQM schemes apply different supervised techniques for TSF [160, 179, 212, 498] and reinforcementbased methods for deducing the increment in the packet drop probability [298, 427, 428, 485, 499].”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [179]
Cites
Random early detection gateways for congestion avoidance
Floyd, S., & Jacobson, V. (1993) · IEEE/ACM Transactions on Networking · doi:10.1109/90.251892 · Cited by 6,290 · see citing works
Analysis and design of controllers for AQM routers supporting TCP flows
Hollot, C. V., Misra, V., Towsley, D., et al. (2002) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2002.1008360 · Cited by 862 · see citing works
Adaptive RED: An Algorithm for Increasing the Robustness of RED's Active Queue Management
Floyd, S., Gummadi, R., & Shenker, S. J. (2001) · Cited by 671 · see citing works
PD-RED: to improve the performance of RED
Sun, J., Ko, K., Chen, G., et al. (2003) · IEEE Communications Letters · doi:10.1109/lcomm.2003.815653 · Cited by 124 · see citing works
Design of a fuzzy controller for active queue management
Fengyuan, R., Yong, R., & Xiuming, S. (2002) · Computer Communications · doi:10.1016/s0140-3664(01)00417-0 · Cited by 75 · see citing works
A genetic algorithm for the design of a fuzzy controller for active queue management
Fatta, G. D., Hoffmann, F., Re, G. L., et al. (2003) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2003.818946 · Cited by 50 · see citing works
Towards fully automated adaptation of RED parameters to optimise TCP performance
Yu, B., & Pitts, J. M. (2006) · Electronics Letters · doi:10.1049/el:20062932 · Cited by 1 · see citing works
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Boutaba, R., Salahuddin, M. A., Limam, N., Ayoubi, S., Shahriar, N., Estrada-Solano, F., & Caicedo, O. M. (2018) · Journal of Internet Services and Applications · doi:10.1186/s13174-018-0087-2 · Cited by 1,036 · see citing works
Li, F., Sun, J., Zukerman, M., Liu, Z., Xu, Q., Chan, S., Chen, G., & Ko, K.-T. (2014) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2014.01.005 · Cited by 33 · see citing works
- Authors
- Hariri, B., & Sadati, N.
- Affiliations
- Sharif University of Technology (IR)
- ORCID
- Sadati, N.
- Venue
- Electronics Letters
- Published
- 2007-09-13
- Volume
- 43
- Issue
- 19
- Pages
- 1053-1055
- ISSN
- 0013-5194 (ISSN-L)
- 1350-911X
- OpenAlex
- W2165862485
- Cited by
- 29
- References
- 7
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 2 · 2022: 2 · 2021: 2 · 2019: 1 · 2018: 2 · 2017: 1 · 2015: 3 · 2014: 3 · 2013: 2
- FWCI
- 2.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Electronics Letters (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- active queue management, artificial neural networks, random early detection, network congestion, queue management
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