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The macroscopic behavior of the TCP congestion avoidance algorithm
Abstract
In this paper, we analyze a performance model for the TCP Congestion Avoidance algorithm. The model predicts the bandwidth of a sustained TCP connection subjected to light to moderate packet losses, such as loss caused by network congestion. It assumes that TCP avoids retransmission timeouts and always has sufficient receiver window and sender data. The model predicts the Congestion Avoidance performance of nearly all TCP implementations under restricted conditions and of TCP with Selective Acknowledgements over a much wider range of Internet conditions.We verify the model through both simulation and live Internet measurements. The simulations test several TCP implementations under a range of loss conditions and in environments with both drop-tail and RED queuing. The model is also compared to live Internet measurements using the TReno diagnostic and real TCP implementations.We also present several applications of the model to problems of bandwidth allocation in the Internet. We use the model to analyze networks with multiple congested gateways; this analysis shows strong agreement with prior work in this area. Finally, we present several important implications about the behavior of the Internet in the presence of high load from diverse user communities.
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Citations
Cited by
Modeling TCP throughput: a simple model and its empirical validation
Padhye, J., Firoiu, V., Towsley, D., & Kurose, J. (1998) · Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication · doi:10.1145/285237.285291 · Cited by 2,106
Promoting the use of end-to-end congestion control in the Internet
Floyd, S., & Fall, K. (1999) · IEEE/ACM Transactions on Networking · doi:10.1109/90.793002 · Cited by 1,646
Online selection of discriminative tracking features
Collins, R. T., Liu, Y., & Leordeanu, M. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.205 · Cited by 1,208
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
RAP: An end-to-end rate-based congestion control mechanism for realtime streams in the Internet
Rejaie, R., Handley, M., & Estrin, D. (1999) · IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320) · doi:10.1109/infcom.1999.752152 · Cited by 710
Roughan, M., Sen, S., Spatscheck, O., & Duffield, N. (2004) · Proceedings of the 4th ACM SIGCOMM conference on Internet measurement · doi:10.1145/1028788.1028805 · Cited by 494
Timely and Continuous Machine-Learning-Based Classification for Interactive IP Traffic
Nguyen, T. T. T., Armitage, G., Branch, P., & Zander, S. (2012) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2012.2187305 · Cited by 156
A Machine Learning Approach to TCP Throughput Prediction
Mirza, M., Sommers, J., Barford, P., & Zhu, X. (2010) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2009.2037812 · Cited by 132
A machine learning approach to improve congestion control over wireless computer networks
Geurts, P., El Khayat, I., & Leduc, G. (2004) · Fourth IEEE International Conference on Data Mining (ICDM'04) · doi:10.1109/icdm.2004.10063 · Cited by 68
On Model Transmission Strategies in Federated Learning With Lossy Communications
Su, X., Zhou, Y., Cui, L., & Liu, J. (2023) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2023.3240883 · Cited by 47
El Khayat, I., Geurts, P., & Leduc, G. (2010) · Wireless Networks · doi:10.1007/s11276-008-0129-y · Cited by 34
Bayesian packet loss detection for TCP
I'onseca, N., & Crovella, M. (2005) · Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies. · doi:10.1109/infcom.2005.1498462 · Cited by 27
Machine-learnt versus analytical models of TCP throughput
El Khayat, I., Geurts, P., & Leduc, G. (2007) · Computer Networks · doi:10.1016/j.comnet.2006.11.017 · Cited by 10
Metadata
- Authors
- Mathis, M., Semke, J., Mahdavi, J., & Ott, T.
- Venue
- ACM SIGCOMM Computer Communication Review
- Published
- 1997-07
- Volume
- 27
- Issue
- 3
- Pages
- 67-82
- ISSN
- 0146-4833 (ISSN-L)
- OpenAlex
- W1990920914
- Cited by
- 1,495
- References
- 0
- FWCI
- 68.52
- Type
- journal article
- Language
- en
- Open access
- closed
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