Programacao genetica aplicada a geracao automatizada de aplicacoes para redes de sensores sem fio

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@MastersThesis{deOliveira:masters,
  author =       "Renato Resende Ribeiro {de Oliveira}",
  title =        "Programacao genetica aplicada a geracao automatizada
                 de aplicacoes para redes de sensores sem fio",
  school =       "Departamento de Ciencia da Computacao, Universidade
                 Federal de Lavras",
  year =         "2014",
  type =         "Mestre",
  address =      "Brazil",
  month =        "13 " # aug,
  keywords =     "genetic algorithms, genetic programming, Rede de
                 sensor sem fio, Middlewares, Wireless sensor network",
  URL =          "http://repositorio.ufla.br/jspui/handle/1/2707",
  size =         "72 pages",
  abstract =     "The wireless sensor networks (WSN) programming is a
                 complex task due to the low-level programming languages
                 and the need of a specific application for each sensor.
                 Furthermore, wireless sensors have many hardware
                 limitations such as low processing power, small memory
                 and energetic limitations. Hence, the automatic
                 programming of WSNs is desirable since it can
                 automatically address these difficulties, besides
                 saving costs by eliminating the need to allocate a
                 developer to program the WSN. The automatic code
                 generation for WSNs using genetic programming has been
                 poorly studied in the literature so far. The genetic
                 programming has proved to be promising in code
                 generation for many application areas. This study
                 proposes the development and application of
                 evolutionary algorithms to generate source codes that
                 solve WSNs problems. The developed evolutionary
                 algorithms should be able to solve different problems
                 of WSNs correctly (achieve the main goal of the
                 problem) and with satisfactory efficiency (mainly on
                 energy savings). The obtained results show that the
                 proposed framework is able to find optimal solutions
                 for the Event Detection Problem for WSN with grid
                 topology and to find satisfactory solutions for WSN
                 with randomised topology. Thus, this study brings many
                 contributions to the WSN area since the automatic
                 programming of WSNs drastically reduces the human
                 programming effort, besides saving costs on executing
                 this task",
  notes =        "in Portuguese",
}

Genetic Programming entries for Renato Resende Ribeiro de Oliveira

Citations