• DocumentCode
    3598204
  • Title

    Uncertainty, protocol behavior prediction through chaos theory?

  • Author

    Kaliappan, Prabhu Shankar

  • Author_Institution
    Dept. of Comput. Sci., Brandenburg Univ. of Technol. Cottbus, Cottbus, Germany
  • Volume
    1
  • fYear
    2011
  • Firstpage
    20
  • Lastpage
    23
  • Abstract
    Heuristic techniques like artificial intelligence, neural networks are applied successfully in the computational field to achieve natural reasoning similar to humans. Among those uncertainty is a prominent factor which is been unsolved. This is a major challenging area in the distributed systems like communications protocol. Moreover practical future prediction is limited to a finite level because the computation requires more system memory. Sometimes it is out of the scope to a normal computer system. Fortunately, nature theory like chaos has a way to overcome this by stating that it is possible to predict the system behavior at an infinite state if a system is deter-ministically modeled. Hence as a multidisciplinary work in this paper we try to identify and extract the similarities between the communications protocol and chaos theory. We also present this promising work to use various nature theories to solve the impenetrable problems in the computational field.
  • Keywords
    chaotic communication; distributed processing; inference mechanisms; neural nets; protocols; uncertainty handling; artificial intelligence; chaos theory; communication protocol behavior prediction; computer system memory; distributed systems; heuristic techniques; natural reasoning; neural networks; uncertainty; Chaos; Equations; Mathematical model; Protocols; Sea measurements; Uncertainty; Unified modeling language; chaos theory; communication protocols; model checking; protocol failures; software design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Uncertainty Reasoning and Knowledge Engineering (URKE), 2011 International Conference on
  • Print_ISBN
    978-1-4244-9985-4
  • Electronic_ISBN
    978-1-4244-9984-7
  • Type

    conf

  • DOI
    10.1109/URKE.2011.6007829
  • Filename
    6007829