Improving TCP in Wireless Networks with an Adaptive Machine-Learnt Classifier of Packet Loss Causes
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Hiding error losses may violate the TCP end-to-end principle as it may require splitting the TCP connection by sending an ACK before the packet arrives at the receiver.
“hiding error losses may violate TCP end-to-end principle as it may require splitting the TCP connection by sending an ACK to the sender before the packet arrives at the receiver [129].”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [129]
The ML-based packet loss classifier is flexible and enables selection between TCP throughput gain and fairness without retraining the classifier.
“Their ML-based packet loss classifier is flexible and enables the selection between TCP throughput gain and fairness without retraining the classifier.”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [129]
All classifiers by El Khayat et al. achieve much higher classification accuracy than non-ML solutions, such as TCP-Veno and TCP-Westwood.
“All the classifiers achieve a much higher classification accuracy than non-ML solutions, such as TCP-Veno and TCP-Westwood.”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [129]
Improved TCP can maintain a fair link share with legacy protocols (TCP-friendly).
“the improved TCP can maintain a fair link share with legacy protocols (i.e.TCPfriendly).”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [129]
Boosting DT with 25 trees provides the highest accuracy and the second fastest training time.
“Boosting DT with 25 trees provide the highest accuracy and the second fastest training time.”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [129]
DT training time is the fastest, with a small reduction in accuracy of less than 4% compared to Boosting DT.
“the training time of DT is the fastest, with a small reduction in accuracy of less than 4% compared to Boosting DT.”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [129]
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Cites
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Modeling TCP Reno performance: a simple model and its empirical validation
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I-TCP: indirect TCP for mobile hosts
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Equation-based congestion control for unicast applications
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A machine learning approach to improve congestion control over wireless computer networks
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Self-citationEfficiency/friendliness tradeoffs in TCP Westwood
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Flagged first, then by citations
Research works printed but not linked: 1
- S. Jaiswal, G. Iannaccone, C. Diot, J. Kurose, and D. Towsley. Measurement and Classification of Out-of-Sequence Packets in a Tier-1 IP Backbone. In Proc. of IEEE INFOCOM, Mar 2003.
Cited by
Sorted by citations
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
Machine-learnt versus analytical models of TCP throughput
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Self-citation
- Authors
- El Khayat, I., Geurts, P., & Leduc, G.
- Affiliations
- University of Liège (BE)
- ORCID
- Geurts, Pierre
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2005
- Pages
- 549-560
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1556516382
- Cited by
- 20
- References
- 18
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 2 · 2020: 2 · 2019: 2 · 2018: 1
- FWCI
- 0.77
- Type
- conference paper
- Language
- en
- Open access
- green
- orbi.uliege.be
- Licence
- other-oa
- Locations
- Lecture notes in computer science (publishedVersion)
- Open Repository and Bibliography (University of Liège) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Networks and Protocols
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Keywords
- TCP, wireless networks, TCP NewReno, link errors, congestion, TCP-friendliness, hybrid wired-wireless networks, supervised learning
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