Rigorous Framework for Distributed Processing with Dynamic Stochastic Information

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-10-M-0066
Agency Tracking Number: O092-SP7-4047
Amount: $99,786.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solitcitation Year: 2009
Solitcitation Topic Code: OSD09-SP7
Solitcitation Number: 2009.2
Small Business Information
Prism Informatix, LLC
5310 N Camino Sumo, Tucson, AZ, 85718
Duns: 830821398
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 John Wissinger
 President
 (520) 991-8381
 john.wissinger@prisminformatix.com
Business Contact
 John Wissinger
Title: President
Phone: (520) 991-8381
Email: john.wissinger@prisminformatix.com
Research Institution
N/A
Abstract
The vast and ever-increasing amount of networked information available creates a growing need for information processing systems that distribute decision making rather than centralize data. But distributed decision systems are notoriously hard to analyze. One reason is that the complexity of the design process encourages the use of ad-hoc methods, so it can easily become impossible to say how well a system actually performs vs. the best that could be done. Prism Informatix proposes to address the need for an optimal framework by extending the rigorous and established theory of distributed hypothesis testing networks. The basic framework has aroused considerable interest because it provides an optimal, analytically tractable, and highly intuitive approach to modeling distributed cooperative (team) decision making under uncertainty. To develop the theory into a practical information processing framework, we modify and extend it to handle real-world stochastic information dynamics, but in a manner that preserves the mathematical structure necessary to support analysis. We implement the new framework in a computational testbed where instrumented analysis studies allow its feasibility to be established.

* information listed above is at the time of submission.

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