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ConnextLogger: Intelligent Data Logging for MDA Modeling and Simulation Systems

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0860-20-C-7119
Agency Tracking Number: B2-2701
Amount: $993,461.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: MDA17-003
Solicitation Number: 17.2
Solicitation Year: 2017
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-07-20
Award End Date (Contract End Date): 2022-07-20
Small Business Information
232 East Java Drive
Sunnyvale, CA 94089
United States
DUNS: 797735883
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Paul Pazandak
 Director of Research
 (408) 990-7471
Business Contact
 Catherine Mekler
Phone: (408) 990-7422
Research Institution

Modeling and Simulation systems, like OSF, can generate incredible amounts of information very quickly; however, the overhead processing required to handle all of this data brings the simulations to their knees. MDA requires an intelligent data logging solution for their modeling & simulation systems that reduces runtime and resource usage (CPU, memory, network, and storage) and collects relevant data, rather than blindly logging all data using a best-effort approach. ConnextLogger is our intelligent, adaptive data-logging platform that will adjust to match the dynamic situation and the analysts’ needs. Our platform will continually collect and asynchronously buffer high fidelity data in circular in-memory caches. This ensures low latency and high throughput while minimizing the impact to the application. The data will be continuously analyzed in real time to intelligently filter out low-valued data. It will seek out anomalies and other events; and, when detected, it will trigger logging of the high-valued, high-fidelity data into permanent-storage. In parallel, a subset of the low-valued data will be logged into permanent-storage even when there are no events or anomalies. This so-called steady state data will provide the analysts needed indicators about the state of the system/objects while minimizing performance impact and resource utilization. Approved for Public Release | 19-MDA-9932 (21 Feb 19)

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

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