Biology-inspired architecture for situation management

Authors:
Kennie H. Jones;Kenneth N. Lodding;Stephan Olariu;Larry Wilson;Chunsheng Xin
Affiliations:
National Aeronautics and Space Administration, Hampton, VA;National Aeronautics and Space Administration, Hampton, VA;Computer Science Department, Old Dominion University, Norfolk, VA;Computer Science Department, Old Dominion University, Norfolk, VA;Computer Science Department, Norfolk State University, Norfolk, VA
Venue:
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Year:
2006

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Abstract

Situation Management is a rapidly developing science combining new techniques for data collection with advanced methods of data fusion to facilitate the process leading to correct decisions prescribing action. Current research focuses on reducing increasing amounts of diverse data to knowledge used by decision makers and on reducing time between observations, decisions and actions. No new technology is more promising for increasing the diversity and fidelity of observations than sensor networks. However, current research on sensor networks concentrates on a centralized network architecture. We believe this trend will not realize the full potential of situation management. We propose a new architecture modeled after biological ecosystems where motes are autonomous and intelligent, yet cooperate with local neighborhoods. Providing a layered approach, they sense and act independently when possible, and cooperate with neighborhoods when necessary. The combination of their local actions results in global effects. While situation management research is currently dominated by military applications, advances envisioned for industrial and business applications have similar requirements. NASA has requirements for intelligent and autonomous systems in future missions that can benefit from advances in situation management. We describe requirements for the Integrated Vehicle Health Management program where our biology-inspired architecture provides a layered approach and decisions can be made at the proper level to improve safety, reduce costs, and improve efficiency in making diagnostic and prognostic assessments of the structural integrity, aerodynamic characteristics, and operation of aircraft.