Controle adaptativo de fluxos de tráfego de redes baseado em modelagem multifractal e sistemas fuzzy

• Autor(a) principal: Cardoso, Alisson Assis
• Data de Publicação: 2019
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/12233
• topic: Controle de fluxos; Redes de comunicações móveis; Modelagem multifractal; Lógica fuzzy; Funções de bases ortonormais; Flow rate control; Mobile communications networks; Multifractal modeling; Fuzzy logic; Ortonormal basis functions; ENGENHARIAS::ENGENHARIA ELETRICA

The network traffic flows that arrive at the base station to be transmitted to the mobile users, in a 5G network system, enter the queuing process until transmission rates are provided. In order to minimize the delay, this work proposes the use of flow control algorithms based on the prediction of user queue behavior. Thus, the more accurate the data prediction, the greater the accuracy and control of flow control algorithms. To improve accuracy, models describing the behavior of network traffic are employed. In this work, two adaptive modeling algorithms based on the Lognormal Beta and BetaMWM models are proposed to model the network traffic and allow its use in real-time applications, such as the 5G network. Simulations are performed in comparisons to multifractal models found in the literature to validate the proposed algorithms, where results in terms of expected value, variance, moments of 2º to 4º order, mean squared errors of autocorrelation and distribution function prove the adaptively use of the algorithms. To perform the flow control, an equation is also proposed to obtain the optimal prediction-based control rate, where generalized ortonormal functions and fuzzy modeling are employed. Simulations of the Downlink 5G link are also performed to validate the proposed flow control algorithms. For this, results in terms of Flow, Utilization, Loss Rate, Delay and Average Waiting Queue are presented, proving the efficiency in the use of multifractal models, orthonormal basis functions, and fuzzy modeling in flow control algorithms for Downlink 5G systems. Taking advantage of the proposed multifractal modeling, an equation is also proposed to estimate the delay limitation for the first recommendations of the 5G network using the network calculation theory. For this, it is proposed a stochastic envelope process for network traffic based on the Adaptive Beta Lognormal model where comparisons with envelope processes known in the literature are performed.