• DocumentCode
    618024
  • Title

    A Genetic Programming based approach to automatically generate Wireless Sensor Networks applications

  • Author

    Resende Ribeiro de Oliveira, Renato ; Heimfarth, Tobias ; Winckler de Bettio, Raphael ; da Silva Arantes, Marcio ; Motta Toledo, Claudio Fabiano

  • Author_Institution
    Dept. of Comput. Sci., Univ. Fed. de Lavras, Lavras, Brazil
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    1771
  • Lastpage
    1778
  • Abstract
    The development of Wireless Sensor Networks (WSNs) applications is an arduous task, since the application needs to be customized for each sensor. Thus, the automatic generation of WSN´s applications is desirable to reduce costs, since it drastically reduces the human effort. This paper presents the use of Genetic Programming to automatically generate WSNs applications. A scripting language based on events and actions is proposed to represent the WSN behavior. Events represent the state of a given sensor node and actions modify these states. Some events are internal states and others are external states captured by the sensors. The genetic programming is used to automatically generate WSNs applications described using this scripting language. These scripts are executed by all network´s sensors. This approach enables the application designer to define only the overall objective of the WSN. This objective is defined by means of a fitness function. An event-detection problem is presented in order to evaluate the proposed method. The results shown the capability of the developed approach to successfully solve WSNs problems through the automatic generation of applications.
  • Keywords
    genetic algorithms; programming languages; telecommunication computing; wireless sensor networks; WSN; arduous task; automatically generate wireless sensor networks applications; cost reduction; event-detection problem; external states; fitness function; genetic programming based approach; internal states; scripting language; sensor node; Genetic algorithms; Genetic programming; Middleware; Sociology; Statistics; Virtual machining; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2013 IEEE Congress on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4799-0453-2
  • Electronic_ISBN
    978-1-4799-0452-5
  • Type

    conf

  • DOI
    10.1109/CEC.2013.6557775
  • Filename
    6557775