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Resource Allocation using Market-Based Optimization (RAMBO)

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-11-C-7526
Agency Tracking Number: B103-002-0105
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: MDA10-002
Solicitation Number: 2010.3
Timeline
Solicitation Year: 2010
Award Year: 2011
Award Start Date (Proposal Award Date): 2011-05-16
Award End Date (Contract End Date): N/A
Small Business Information
625 Mount Auburn Street, Cambridge, MA, -
DUNS: 115243701
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Chris Farnham
 Senior Software Engineer
 (617) 491-3474
 cfarnham@cra.com
Business Contact
 Ninos Hanna
Title: Contract Specialist
Phone: (617) 491-3474
Email: nhanna@cra.com
Research Institution
 Stub
Abstract
Missile defense takes place in a dynamic, uncertain environment. Multi-raid attacks threaten to overload sensor capabilities, leaving fewer sensor resources free to observe each target complex. Moreover, the shift in emphasis toward early intercept, coupled with the growing importance of short- and medium-range threats, reduces the time available for detection, tracking, and discrimination, because engagement decisions must be made more quickly. These factors increase the need for effective sensor resource management to squeeze the maximum amount of useful information out of an overloaded sensor network. What is needed is a solution that can optimally assign a large number of heterogeneous sensors to a large number of incoming threats fast enough for early intercept, while meeting dynamic constraints on sensor availability and physical constraints. Here, we propose Resource Allocation using Market-Based Optimization (RAMBO), to provide dynamic planning and scheduling of sensors to maximize sensor quality of service while minimizing sensor uncertainty. This approach applies market-based optimization, using solutions from economic theory and game theory, to sensor resource management by creating an artificial market for sensor capabilities and information. With a properly designed market, we can engineer a system that ensures an optimal allocation of sensors and resources.

* Information listed above is at the time of submission. *

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