Genetic algorithm-based congestion control optimisation for mobile data network

Autor: Yushuang Wang, Yongli Xing
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Applied Mathematics and Nonlinear Sciences, Vol 8, Iss 1, Pp 2405-2412 (2023)
Druh dokumentu: article
ISSN: 2444-8656
DOI: 10.2478/amns.2021.2.00309
Popis: Mobile data network is featured by long delay and moving terminals, which affect the user service quality performance of transmission control protocol’s (TCP) congestion control algorithm Vegas. To solve this problem, this paper first proposed to optimise the congestion control algorithm using a genetic algorithm, build ns-3 network topology structure and adopt mobile data network trace for optimisation and simulation; and the Vegas optimisation problem as a multivariate dual-objective problem was solved with Non-dominated Sorting Genetic Algorithm II (NSGA-II). The ns-3 simulation results indicate that Vegas with optimised parameters have high throughput and short delay, which significantly promotes TCP Vegas’s QoS under a mobile scene.
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