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Multi-Scale, Multi-Resolution Network Information Flow Monitoring and Understanding

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-10-C-0162
Agency Tracking Number: F09B-T15-0271
Amount: $100,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF09-BT15
Solicitation Number: 2009.B
Solicitation Year: 2009
Award Year: 2010
Award Start Date (Proposal Award Date): 2010-07-15
Award End Date (Contract End Date): 2011-04-15
Small Business Information
15400 Calhoun Drive Suite 400
Rockville, MD 20855
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Jason Li
 Director of Networks and Security
 (301) 294-5275
Business Contact
 Mark James
Title: Director of Contracts and Proposals
Phone: (301) 294-5221
Research Institution
 Princeton University
 Mung Chiang
School of Eng. and Applied Sci Engineering Quadrangle
Princeton, NJ 8594
United States

 (609) 258-5071
 Nonprofit College or University

Communication networks can be viewed and analyzed as information flows, which can be better understood with practical design guidelines by capturing the complex interactions across essential network properties and tasks. Intelligent Automation Inc. and its subcontractor propose a novel unifying approach for multi-scale, multi-resolution network information flow modeling and analysis. We introduce a three-dimensional mechanism for network monitoring and understanding with tunable resolution. The three dimensions are time, space, and frequency, which broadly represent the time-series analysis, topological properties, and network dynamics, respectively. Our approach will exploit the correlations of all dimensions to understand the geometry of network data. Network coding will be applied broadly as a general networking paradigm to support our network monitoring/analysis approach based on the high-dimensional network data collected in multiple resolutions. Our innovation is to infer network through a network task over different scales and resolutions, then feed the network information back to the underlying network protocol, thereby stabilizing the network monitoring operation and optimizing the network protocol. Geometric structures of the network optimization problem will be utilized. Our network monitoring/analysis approach operates without fixed traffic parameterization and extends local network deployment and measurement to network-wide property and management policies. BENEFIT: The proposed effort will provide a unifying framework that enables holistic understanding of network information flows that span different resolutions and time-scales. Such insights will benefit various applications including routing, resource allocation, and performance analysis in mobile, heterogeneous Airborne Networks. Besides military networks, such insights are also directly beneficial to various heterogeneous networks. Potential commercial applications include border and coast patrol, law enforcement agency, emergency control center, and various civil applications, possibly with huge amount of users. The size of the market is quite large and may grow rapidly with the demand in wireless network reliability and availability. We expect that the aggregate market size will be similar to or larger than that of military applications. Such a large market need will help attract a great amount of potential investment. IAI is more than a “think tank”, and we have actively pursued with our partners the application of our technologies into actual products in the past. For this proposed effort, in particular, we strongly believe that our work provides the solution needed in both research community and in practice. In addition, IAI will closely work with our partners and collaborator companies such as Raytheon, BAE systems, Lockheed, Boeing, and Telcordia to transfer this technology into the military and commercial world.

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

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