Topological Robust Algorithms for Massive Data Sets via Agent-based Modular Infrastructure (TA-DA) Supporting Decentralized and Parallel Processing

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$739,929.00
Award Year:
2012
Program:
SBIR
Phase:
Phase II
Contract:
N00014-12-C-0264
Agency Tracking Number:
O2-1249
Solicitation Year:
2010
Solicitation Topic Code:
OSD10-L07
Solicitation Number:
2010.2
Small Business Information
Intelligent Automation, Inc.
15400 Calhoun Drive, Suite 400, Rockville, MD, -
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
Y
Duns:
161911532
Principal Investigator:
Onur Savas
Research Scientist
(301) 294-4241
osavas@i-a-i.com
Business Contact:
Mark James
Director, Contract&Prop
(301) 294-5221
mjames@i-a-i.com
Research Institution:
Stub




Abstract
This project aims at building a modular component that can be part of a future end-to-end system with capability of distilling, analyzing, discovering, structuring, and interpreting relevant information hidden in massive data that is already stored in distributed multi-INT databases including but not limited to social network data, ISR sensor data, and Internet traffic data. Our approach is based on topological data analysis, a method that focuses on recovering the topology of noisy data points, sampled from an unknown space, and embedded in a high-dimensional space. Based on our preliminary analysis in Phase I, we will continue our efforts for constructing combinatorial representations of point sets, as well as developing algorithms for effective computation of robust topological invariants. Emphasis will be on supporting decentralized and parallel processing such that the modular system can be deployed on clusters of computers. Then cluster-based computing approaches such MapReduce in a Hadoop-based ecosystem can be used to wrap the algorithms and implement using open-source software.

* information listed above is at the time of submission.

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