• DocumentCode
    3010097
  • Title

    New Results in Understanding Performance and Vulnerability in Complex Networks

  • Author

    Repperger, Daniel W.

  • Author_Institution
    Air Force Research Laboratory - Dayton, Ohio
  • fYear
    2007
  • fDate
    20-23 June 2007
  • Abstract
    New results can be obtained about performance and vulnerability of complex networks through the common intersection of the fields of graph theory, information theory, and optimization theory. Graph theory provides a basis of architecture and also constraint relationships for key flow variables. Information theory provides measures and metrics of flow performance. The optimization of complex networks is accomplished via genetic algorithms on the flow variables. By performing a minimum flow and maximum flow optimization, a sensitivity matrix of vulnerabilities of a network can be ascertained. Thus the most vulnerable set of nodes can be determined. This procedure is first applied to a logistics network. The generalization to communication´s networks and other distributed complex systems is discussed.
  • Keywords
    Biomedical engineering; Complex networks; Control theory; Councils; Engineering in medicine and biology; Genetic communication; Graph theory; Information theory; Laboratories; Man machine systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Robotics and Automation, 2007. CIRA 2007. International Symposium on
  • Conference_Location
    Jacksonville, FL, USA
  • Print_ISBN
    1-4244-0790-7
  • Electronic_ISBN
    1-4244-0790-7
  • Type

    conf

  • DOI
    10.1109/CIRA.2007.382833
  • Filename
    4269833