Modelagem multifractal aplicada à estimação de probabilidade de perda de dados e ao controle de fluxos de tráfego em redes

• Autor(a) principal: ROCHA, Flávio Geraldo Coelho
• Data de Publicação: 2011
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• dARK ID: ark:/38995/0013000000pk9
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tde/967
• topic: Tráfego de redes; Análise multifractal, Probabilidade de perda; 1. Telecomunicações; 2. Redes de computadores; 3. Multifractais; Network traffic; Multifractal analysis; Loss probability; CNPQ::ENGENHARIAS

In this dissertation, the multifractal analysis is used in the context of traffic modeling of communications networks by proposing algorithms and techniques for improving the performance of these networks. Thus, in order to better describe traffic networks, a model based on multifractal multiplicative cascade that uses autoregressive processes for multipliers modeling is proposed, the model is called CMAM (Multifractal Cascade with Multipliers Autoregressive Modeling). Simulations are carried out to evaluate the model performance on describing real video traffic traces and wired and wireless real network traffic traces. In addition, considering data loss probability as an important quality of service measure, a mathematical expression for estimating loss probability that takes into account wavelet coefficients associated to the traffic process is proposed. The expression is evaluated, among other ways, through simulations in a wireless network scenario based on OFDM / TDMA technologies. Then, an admission control scheme for network flows which is based on the proposed loss probability estimation is presented and applied to the scenario considered. Simulations show efficiency of the proposed scheme in comparison to other approaches found in the literature. In addition, an adaptive transmission rate allocation scheme that considers the characteristics of multifractal network traffic is proposed, which one is compared to an approach that considers the monofractal traffic properties. Finally, using CMAM for video traffic modeling, a rate control algorithm for video traffic in the source is presented based on exponential modeling of the scale function associated with the quantization parameter Q of the video encoder.