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%.

Genetic Improvement of TCP Congestion Avoidance / Carbognin, Alberto; Custode, Leonardo Lucio; Iacca, Giovanni. - 13627:(2022), pp. 114-126. (Intervento presentato al convegno BIOMA 2022 tenutosi a Maribor nel 17th -18th November 2022) [10.1007/978-3-031-21094-5_9].

Genetic Improvement of TCP Congestion Avoidance

Custode, Leonardo Lucio;Iacca, Giovanni
2022-01-01

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%.
2022
Bioinspired Optimization Methods and Their Applications (BIOMA) 2022
Cham, Svizzera
Springer
978-3-031-21093-8
978-3-031-21094-5
Carbognin, Alberto; Custode, Leonardo Lucio; Iacca, Giovanni
Genetic Improvement of TCP Congestion Avoidance / Carbognin, Alberto; Custode, Leonardo Lucio; Iacca, Giovanni. - 13627:(2022), pp. 114-126. (Intervento presentato al convegno BIOMA 2022 tenutosi a Maribor nel 17th -18th November 2022) [10.1007/978-3-031-21094-5_9].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/357523
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