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Genetic Improvement of TCP Congestion Avoidance

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Bioinspired Optimization Methods and Their Applications (BIOMA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13627))

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Abstract

The Transmission Control Protocol (TCP) protocol, i.e., one of the most used protocols over networks, has a crucial role on the functioning of the Internet. Its performance heavily relies on the management of the congestion window, which regulates the amount of packets that can be transmitted on the network. In this paper, we employ Genetic Programming (GP) for evolving novel congestion policies, encoded as C++ programs. We optimize the function that manages the size of the congestion window in a point-to-point WiFi scenario, by using the NS3 simulator. The results show that, in the protocols discovered by GP, the Additive-Increase-Multiplicative-Decrease principle is exploited differently than in traditional protocols, by using a more aggressive window increasing policy. More importantly, the evolved protocols show an improvement of the throughput of the network of about 5%.

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Notes

  1. 1.

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Authors and Affiliations

  1. Department of Information Engineering and Computer Science, University of Trento, Trento, Italy

    Alberto Carbognin, Leonardo Lucio Custode & Giovanni Iacca

Authors
  1. Alberto Carbognin
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  2. Leonardo Lucio Custode
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  3. Giovanni Iacca
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Corresponding author

Correspondence to Giovanni Iacca .

Editor information

Editors and Affiliations

  1. University of Maribor, Maribor, Slovenia

    Marjan Mernik

  2. Jožef Stefan Institute, Ljubljana, Slovenia

    Tome Eftimov

  3. University of Maribor, Maribor, Slovenia

    Matej Črepinšek

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Carbognin, A., Custode, L.L., Iacca, G. (2022). Genetic Improvement of TCP Congestion Avoidance. In: Mernik, M., Eftimov, T., Črepinšek, M. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2022. Lecture Notes in Computer Science, vol 13627. Springer, Cham. https://doi.org/10.1007/978-3-031-21094-5_9

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  • DOI: https://doi.org/10.1007/978-3-031-21094-5_9

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