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Intelligent Network Configuration Optimization Toolkit (INCOT)

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: F30602-02-C-0026
Agency Tracking Number: 011IF-0265
Amount: $749,999.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 2002
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
1660 So. Amphlett Blvd. , Suite 350
San Mateo, CA 94402
United States
DUNS: 608176715
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Robert Richards
 Principal Investigator
 (650) 655-7242
Business Contact
 Melissa Thiemmedh
Title: Lead Accountant
Phone: (650) 655-7242
Research Institution

SHAI, in cooperation with our subcontractor, OPNET Technologies, Inc., propose to continue our development of an innovative Artificial Intelligence (AI) toolkit interface to OPNET's Modeler and other networking COTS products, to configure and optimizenetwork configuration and operations in the field. This Intelligent Network Configuration Optimization Toolkit (INCOT) will allow for rapid design and optimization of communications networks without requiring the user to have programming skills orknowledge of the underlying OPNET network simulation tools. Because developing INCOT represents a challenge, we utilized and propose to continue to pursue an integrated approach drawing upon a broad range of AI techniques, user interface, andvisualization technologies. There is currently a great need for any solution that will dramatically reduce the complexity of network configuration due to the great quantity and diversity of information that must be analyzed, as well as the short decisioncycles.The resulting system will provide the capability for less experienced network engineers to perform efficient and effective network engineering and ongoing operations, with the end result being reduced costs, increased operational efficiency, and improvedrobustness. We will build upon the Phase I results, including the phase I prototype, and iteratively build a more complete and robust Phase II prototype.

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

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