Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 6, Issue 2


Published
on

December 12, 2022


Pages

2405-2412


DOI

Article

Genetic algorithm-based congestion control optimisation for mobile data network


Authors

Wang Yushuang Affiliation:
China University of Geosciences, Beijing 10083, China
and Xing Yongli Affiliation:
China University of Geosciences, Beijing 10083, China


Abstract

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.


Keywords

Mobile cellular networks, Congestion control, TCP Vegas, NSGA-II, ns-3


Citation

Yushuang, W. & Yongli, X. (2021). Genetic algorithm-based congestion control optimisation for mobile data network. Applied Mathematics and Nonlinear Sciences, 6(2), 2405–2412. https://doi.org/10.2478/amns.2021.2.00309
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