Saturday, December 13, 2014

Priority #3 Training Component



Priority #3 Training Component

1)      Overt, highly visible "SIM MODE" banner or background display to clearly distinguish between simulated and live operations
2)      Ability to simulate interface link capabilities and create anomalies found in real-world operation to aid in interface control troubleshooting
3)      Be engineered such that training data shall be protected against inadvertently transmitting any simulation generated track data onto any live MTN (threshold)
4)      Be compliant with Defense Modeling and Simulation Office (DMSO) high-level architecture requirements to enable applications to function in a distributed manner
a)      Password/profile protected for ICO position
i)        Tailorable user permissions, preferences for other users
5)      Ability to conduct individual training for other data links such as SADL
6)      Records real-world track data to generate scenarios for test simulations, analysis and training, using playback when required
7)      Able to inject dynamic "on the fly" tracks/anomalies and other network issues even in playback mode with the ability to save newly created scenario(s).
8)      Able to import previously recorded live network operations for simulation mode/training with the ability to inject and manipulate data and use management tools to replicate real world management/actions/analysis
9)      Able to export recordings to distant users for use in analysis and data link management training
10)  Scenario generation mode provides all tools and objects for generating, displaying and storing scenarios for future use, to include adding dynamically generated tracks to previously recorded track data
11)  Ability to generate all of the anomalies the MTN Monitoring and Analysis component is programmed to detect, as well as simulate anomalies operators could expect to detect manually
12)  Directly interoperable with the MTN Monitoring and Analysis component - allowing for monitoring and analysis training of real-world track data and injected anomalies as created by the MTN training component.

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