Resource Allocation using Market-Based Optimization (RAMBO)

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$999,966.00
Award Year:
2013
Program:
SBIR
Phase:
Phase II
Contract:
HQ0147-13-C-7110
Award Id:
n/a
Agency Tracking Number:
B2-1837
Solicitation Year:
2010
Solicitation Topic Code:
MDA10-002
Solicitation Number:
2010.3
Small Business Information
MA, Cambridge, MA, 02138-4555
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
115243701
Principal Investigator:
SctottReilly
Principal Scientist
(617) 491-3474
snealreilly@cra.com
Business Contact:
MarkFelix
Contracts Manager
(617) 491-3474
mfelix@cra.com
Research Institute:
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. 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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