A survey of evolutionary and embryogenic approaches to autonomic networking

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@Article{Miorandi2009,
  author =       "Daniele Miorandi and Lidia Yamamoto and 
                 Francesco {De Pellegrini}",
  title =        "A survey of evolutionary and embryogenic approaches to
                 autonomic networking",
  journal =      "Computer Networks",
  year =         "2010",
  volume =       "54",
  number =       "6",
  pages =        "944--959",
  month =        "29 " # apr,
  ISSN =         "1389-1286",
  DOI =          "doi:10.1016/j.comnet.2009.08.021",
  URL =          "http://www.sciencedirect.com/science/article/B6VRG-4X6FNS9-2/2/9be45a6ee371c9df9bae76c468300991",
  keywords =     "genetic algorithms, genetic programming, Autonomic
                 networking, Evolutionary computation, Genetic
                 Algorithm, Chemical computing, Artificial
                 embryogenies",
  abstract =     "The term 'autonomic networking' refers to
                 network-level software systems capable of
                 self-management, according to the principles outlined
                 by the Autonomic Computing initiative. Autonomicity is
                 widely recognized as a crucial property to harness the
                 growing complexity of current networked systems.

                 In this paper, we present a review of state-of-the-art
                 techniques for the automated creation and evolution of
                 software, with application to network-level
                 functionalities. The main focus of the survey are
                 biologically-inspired bottom-up approaches, in which
                 complexity is grown from interactions among simpler
                 units. First, we review evolutionary computation,
                 highlighting aspects that apply to the automatic
                 optimisation of computer programs in online, dynamic
                 environments. Then, we review chemical computing,
                 discussing its suitability as execution model for
                 autonomic software undergoing self-optimization by code
                 rewriting. Last, we survey approaches inspired by
                 embryology, in which artificial entities undergo a
                 developmental process. The overview is completed by an
                 outlook into the major technical challenges for the
                 application of the surveyed techniques to autonomic
                 systems.",
}

Genetic Programming entries for Daniele Miorandi Lidia Yamamoto Francesco De Pellegrini

Citations