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Previous issue date: 2014-06-26 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Inthispaperweproposeafuzzymodel,calledFuzzyLMScomAutocorrela¸c˜aoMultifractal,
whose weights are updated according to information from multifractal traffic modeling.
These weights are calculated by incorporating an analytical expression for the autocorrelation function of a multifractal model in the training algorithm of the fuzzy model that is based on the Wiener-Hopf filter. We evaluate the prediction performance of the proposed network traffic prediction algorithm with respect to other predictors. Further, we propose a bandwidth allocation scheme for network traffic based on the fuzzy prediction algorithm. Comparisons with other bandwidth allocation schemes in terms of byte loss rate, link utilization, buffer occupancy and average queue size verifies the efficiency of the proposed scheme. Also, We propose an other adaptive fuzzy algorithm, called Fuzzy-LMS-OBF com alfa adaptivo , for traffic flow control described by theβMWM model. The proposed
algorithm uses Orthonormal Basis Functions (OBF) and its training based on the LMS
algorithm. We also present an expression for the optimal traffic source rate derived from
Fuzzy LMS. Then, we evaluate the performance of the Fuzzy-LMS-OBF com alfa adaptivo
algorithm with respect to other methods. Through simulations, we show that the proposed
control scheme is benefited from the superior performance of the proposed fuzzy algorithm.
Comparisons with other methods in terms of mean and variance of the queue size in the
buffer, Utilization rate of the link, Loss rate and Throughput are presented. / Neste trabalho propomos um modelo fuzzy, nomeado Fuzzy LMS com Autocorrela¸c˜ao Multifractal, cujos pesos s˜ao calculados atrav´es de informa¸c˜oes provindas da an´alise multifractal de s´eries temporais. Esses pesos s˜ao encontrados incorporando uma express˜ao anal´ıtica para a fun¸c˜ao de autocorrela¸c˜ao de um modelo multifractal no algoritmo de treinamento do modelo fuzzy que tem como base o filtro de Wiener-Hopf. Avaliamos ent˜ao o desempenho de predi¸c˜ao de tr´afego de redes do modelo fuzzy proposto adaptativo com
rela¸c˜ao a outros preditores. Em seguida, propomos um esquema de aloca¸c˜ao de banda para tr´afego de redes baseado no algoritmo Fuzzy LMS com Autocorrela¸c˜ao Multifractal. Compara¸c˜oes com outros esquemas de aloca¸c˜ao de banda em termos de taxa de perda de bytes, utiliza¸c˜ao do enlace, ocupa¸c˜ao do buffer e tamanho m´edio da fila comprovam a eficiˆencia do algoritmo no esquema utilizado. Al´em disso, propomos um outro algoritmo fuzzy adaptativo para controle de fluxos de tr´afego que podem ser descritos pelo modelo multifractalβMWM, que chamamos de Fuzzy-LMS-OBF com alfa adaptivo, o qual utiliza
Fun¸c˜oes de Bases Ortonormal (FBO) e tem como base de treinamento, o algoritmo LMS. Propomos tamb´em uma equa¸c˜ao para c´alculo da taxa ´otima de controle derivada do modelo Fuzzy LMS. Em seguida, avaliamos o desempenho do algoritmo de controle adaptativo proposto com rela¸c˜ao a outros m´etodos. Atrav´es de simula¸c˜oes, mostramos que os esquemas de controle e aloca¸c˜ao de taxa se favorecem do desempenho dos algoritmos fuzzy adaptativos propostos. Compara¸c˜oes com outros m´etodos em termos de tamanho m´edio e variˆancia da fila no buffer, Taxa de Utiliza¸c˜ao do enlace e Vaz˜ao s˜ao apresentadas.
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.bc.ufg.br:tede/3164 |
| Date | 26 June 2014 |
| Creators | Cardoso, Alisson Assis |
| Contributors | Vieira, Flávio Henrique Teles, Vieira, Flávio Henrique Teles, Carvalho, Cedric Luiz de, Brito, Leonardo da Cunha |
| Publisher | Universidade Federal de Goiás, Programa de Pós-graduação em Engenharia Elétrica e da Computação (EMC), UFG, Brasil, Escola de Engenharia Elétrica, Mecânica e de Computação - EMC (RG) |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | Portuguese |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Format | application/pdf |
| Source | reponame:Biblioteca Digital de Teses e Dissertações da UFG, instname:Universidade Federal de Goiás, instacron:UFG |
| Rights | http://creativecommons.org/licenses/by-nc-nd/4.0/, info:eu-repo/semantics/openAccess |
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