• DocumentCode
    2718570
  • Title

    Modeling for NASA Autonomous Nano-Technology Swarm Missions and Model-Driven Autonomic Computing

  • Author

    Hinchey, Mike ; Dai, Yuan-Shun ; Rouff, C.A. ; Rash, James L. ; Qi, Mingrui

  • Author_Institution
    Comput. Sci. Dept., Loyola Coll. in Maryland, Baltimore, MD
  • fYear
    2007
  • fDate
    21-23 May 2007
  • Firstpage
    250
  • Lastpage
    257
  • Abstract
    NASA ANTS autonomous nano-technology swarm missions will be operating in the universe, and therefore rely much on high autonomy. This paper presents a novel technology for NASA´s ANTS missions, named as model-driven autonomic computing. As the foundation for the technology, a new model is constructed for the ANTS system. Exceeding other existent models, the new hierarchical model overcomes the challenges of largeness, complexity, dynamicity and unexpectedness possessed by the ANTS system. Then, the paper exhibits the structure and functions of virtual neuron that is basic unit together with the model for the model-driven autonomic technology in ANTS missions. The paper also deploys self-configuration, self-healing, self-optimization and self-protection for ANTS. A case study, examples and simulations are illustrated.
  • Keywords
    aerospace computing; fault tolerant computing; nanotechnology; NASA autonomous nanotechnology swarm missions; hierarchical model; model-driven autonomic computing; model-driven autonomic technology; Autonomic nervous system; Biology computing; Computer science; Educational institutions; NASA; Neurons; Particle swarm optimization; Space technology; Space vehicles; Tree data structures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Information Networking and Applications, 2007. AINA '07. 21st International Conference on
  • Conference_Location
    Niagara Falls, ON
  • ISSN
    1550-445X
  • Print_ISBN
    0-7695-2846-5
  • Type

    conf

  • DOI
    10.1109/AINA.2007.93
  • Filename
    4220901