DECOM - Trabalhos apresentados em eventos

URI permanente para esta coleçãohttp://www.hml.repositorio.ufop.br/handle/123456789/581

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2009 - 200912010 - 20111

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Autor: search.filters.author.Guimarães, Frederico GadelhaTem arquivos: Sim

Resultados da Pesquisa

Agora exibindo 1 - 2 de 2
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    Evolutionary design of wireless sensor networks based on complex networks.
    (2009) Ruela, André Siqueira; Cabral, Raquel da Silva; Aquino, André Luiz Lins de; Guimarães, Frederico Gadelha
    This work proposes a genetic algorithm for design-ing a wireless sensor network based on complex network theory. We develop an heuristic approach based on genetic algorithms for finding a network configuration such that its communication structure presents complex network characteristics, e.g. a small value for the average shortest path length and high cluster coefficient. The work begins with the mathematical model of the hub location problem, developed to determine the nodes which will be configured as hubs. This model was adopted within the genetic algorithm. The results reveal that our methodology allows the configuration of networks with more than a hundred nodes with complex network characteristics, thus reducing the energy consumption and the data transmission delay.
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    Um algoritmo coevolutivo cooperativo para configuração de uma rede de sensores sem fio.
    (2011) Ruela, André Siqueira; Aquino, André Luiz Lins de; Guimarães, Frederico Gadelha; Freitas, Alan Robert Resende de
    This work proposes a cooperative coevolutionary algorithm for design of a wireless sensor network considering complex network metrics. It is proposed a heuristic to find a network configuration such that its communication structure presents a small value for the average shortest path length and a high cluster coefficient. This configuration considers a cluster based network, where the cluster heads have two communication radii. We describe how the problem can be partitioned and how the fitness computation can be divided such that the cooperative coevolution model is feasible. The results reveal that our methodology allows the configuration of networks with more than a hundred nodes with two specifics complex network measurements allowing the reduction of energy consumption and the data transmission delay.