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Intelligent Network Configuration Optimization Toolkit (INCOT) Overview and Phase I Prototype Briefing

This briefing outlines the Intelligent Network Configuration Optimization Toolkit (INCOT) Phase I prototype, developed through a collaboration between SHAI and OPNET Technologies. It reviews the project's objectives, architecture, and the integration of AI techniques to optimize network configurations. The document highlights SHAI’s background in AI consulting and OPNET’s expertise in predictive network management. It details the INCOT workflow, the design of a proof-of-concept prototype, and discusses commercialization opportunities, risks, and issues for further development.

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Intelligent Network Configuration Optimization Toolkit (INCOT) Overview and Phase I Prototype Briefing

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  1. Intelligent Network Configuration Optimization Toolkit (INCOT) Phase I SBIR Prototype Briefing2001 November Robert Richards Paul Janes SHAI OPNET Technologies Stottler Henke Associates, Inc. 1660 South Amphlett Blvd., Suite 350 San Mateo, CA 94402 650-655-7242 FAX: 650.655-7243 richards@shai.com www.shai.com OPNET Technologies, Inc. 7255 Woodmont Avenue Bethesda, MD 20814 240-497-3000 Fax: (240) 497-3001 pjanes@opnet.com www.opnet.com

  2. Overview • SHAI background • OPNET background • Related Projects • Objectives • Architecture • AI & other techniques • Task schedule • Commercialization • Issues and concerns

  3. SHAI Background • AI R&D consulting firm, founded in 1988 • Artificial Intelligence Professionals • AI Projects – over 100 • Variety of AI Techniques

  4. Why Partnering with OPNET • Leader in predictive network management software for network design, deployment, and operations. • Proven technology: Since 1987 thousands of organizations have used OPNET Modeler • OPNET products designed to be enhanced by third parties.

  5. Related Projects • Decision support system to assist LSOs land aircraft on aircraft carriers (SHAI) • NETWARS: Assists in communications burden analysis, and contingency analysis. Interfaces with OPNET Modeler (OPNET)

  6. Objectives • Develop AI interface to OPNET Modeler to configure & optimize networks in the field • Via • Expert knowledge of devices • Adherence to policies • Goal directed optimization • Interactive with user

  7. Phase I Objectives • Requirements • Knowledge engineering • Determine AI techniques • Design Phase II system • Goals, features, methodology, algorithms, user interface, supported network protocols/types • Implement proof-of-concept prototype

  8. Overall Architecture

  9. Phase I Prototype Architecture Relative to Overall Architecture

  10. OPNET Modeler, with the following add-on modules Radio Terrain Modeling OPNET Development Kit (ODK) OPNET in Implementation

  11. Air Force Deployable Communications Architecture

  12. Scenariofor Network Engineer • Rapidly deploy a camp in Afghanistan • 2 geographically separated sub-networks connected via line-of-site microwave connection • 1 sub-network has satellite link

  13. INCOT Workflow • Drill down to deployment location • Select the closest pre-built generic network layout to deployment • Adjust sub-network locations • Add or remove components easily via customized palettes of available components. • Verify links

  14. INCOT Workflow (cont.) • Have INCOT automatically determine a viable location for the satellite uplink • Review terrain profile between antennae • Have INCOT automatically determine viable microwave antennae locations • Analyze the network • Modify if necessary.

  15. Major INCOT Enhancements • Simplified Iconized workflow • Pre-built network with pre-configured sub-networks • RULES: Automated rules and algorithms to determine • satellite uplink location • line-of-sight antennae locations • Customized palette to provide only available options

  16. Satellite Uplink without INCOT • User needs to understand Modeler, including the Radio and Terrain modules • Every attempted location requires a simulation run, which the user needs to know how to perform properly and needs to know how to interpret. • To make the solution easier, user inclined to place higher on the hill than necessary

  17. Review of Demonstration & Architecture

  18. Phase I Proves SHAI/OPNET Approach • Collaboration risk • Synergy not Quagmire • Phase II prototype can & should be deployed • Commercialization • Framework • Actual knowledge

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