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
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;
Conference_Titel :
Advanced Information Networking and Applications, 2007. AINA '07. 21st International Conference on
Conference_Location :
Niagara Falls, ON
Print_ISBN :
0-7695-2846-5
DOI :
10.1109/AINA.2007.93