Loughborough University
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Revisiting legacy high-speed TCP congestion control variants: An optimisation-theoretic analysis of multi-mode TCP

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journal contribution
posted on 2022-08-26, 08:14 authored by Talal A Edwan, Iain PhillipsIain Phillips, Lin GuanLin Guan, Jon Crowcroft, Ashraf Tahat, Bashar EA Badr
We revisit the problem of link capacity under-utilisation in TCP Congestion Control (TCP-CC) when working in High-Bandwidth-Delay-Product (High-BDP) networks. We approach this problem using a multi-mode approach and propose TCP-Gentle as an example of TCP-CC that uses this approach. While General Additive Increase Multiplicative Increase (GAIMD) congestion control algorithms received a lot of attention in the literature, little was mentioned about modelling multi-mode GAIMD. To this aim, we provide a tractable optimisation-theoretic model for TCP-Gentle which can be generalised to any multi-mode GAIMD. We show through analysis, simulation, and real-test-bed experiments of single flow, double flow, and single flow with background web traffic, that the proposed TCP-Gentle is competitive with existing TCP variants. Particularly, under certain assumption, TCP-Gentle can outperform TCP-YeAH in terms of fairness to TCP-NewReno. Besides, the proposed TCP-Gentle is more gentle to network; it maintains minimal average queues of less than 1.5% of pipe's BDP, and reassembles to a great extent a highly-concave congestion window.

Funding

Loughborough University

History

School

  • Science

Department

  • Computer Science

Published in

Simulation Modelling Practice and Theory

Volume

118

Issue

2022

Publisher

Elsevier

Version

  • AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Simulation Modelling Practice and Theory and the definitive published version is available at https://doi.org/10.1016/j.simpat.2022.102542

Acceptance date

2022-03-26

Publication date

2022-04-14

Copyright date

2022

ISSN

1569-190X

Language

  • en

Depositor

Dr Lin Guan. Deposit date: 25 August 2022

Article number

102542