Biology-Inspired Networking.

The article discusses a networking algorithm modeled on a fruit fly's neurology, developed in part by Carnegie-Mellon University professor Ziv Bar-Joseph, that may render traditional methods for determining peer relationships in groups obsolete. The article describes the methodology of applying mole...

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Publicado en:Communications of the ACM Vol. 54; no. 6; pp. 11 - 14
Autor principal: Kroeker, Kirk L.
Formato: Artículo
Publicado: Association for Computing Machinery Jun2011
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1145/1953122.1953128
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        atl: Biology-Inspired Networking.
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        au: Kroeker, Kirk L.
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        Algorithms
        Neurosciences
        Bar-Joseph, Ziv
        Molecular models
        Structural frame models
        Sensor networks
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          Algorithms
          Neurosciences
          Bar-Joseph, Ziv
          Molecular models
          Structural frame models
          Sensor networks
      ab: The article discusses a networking algorithm modeled on a fruit fly's neurology, developed in part by Carnegie-Mellon University professor Ziv Bar-Joseph, that may render traditional methods for determining peer relationships in groups obsolete. The article describes the methodology of applying molecular mechanism research to scientific networking, including the creation of a maximal independent set (MIS) of leader nodes that can communicate with the rest of the network. According to the article, the algorithm adapts well to sensor networks. The article states that Bar-Joseph and colleagues are attempting to determine how cellular failure can give insight about computer network backup.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
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