System-of-Systems Modeling and Analysis
The science of System-of-Systems (SoS) is still in its infancy and thus concurrence on a single definition has yet to occur. However, there are common themes among the diverse definitions. The first is the assumption that individual systems must have their own independent operational capability. The individual systems may be, but are not required to be, geographically dispersed. This is part of what makes a SoS complex in nature. Finally, the individual systems form into a SoS with emergent behaviors and capabilities that couldn't exist independently.
There are many examples of what academics and industry leaders refer to as a SoS. Consider a combat team during a high intensity mission. Several different systems and technologies must come together in order to defeat an enemy or achieve an objective. Another example is the air transportation industry. There are many technologies that support navigation, weather, and communications for hundreds of systems dispersed all over the globe.
Why is System-of-Systems analysis important?
- Systems are becoming increasingly complex and interdependent
- The ability to assess and predict SoS effectivenes is essential for critical business decisions
- Many challenges in government, industry and national security are cross-disciplinary and based upon collections of systems working synergistically
What are the objectives for developing this capability?
- Create the ability to capture key system interdependencies and measure effectiveness at the SoS level
- Capture true SoS performance for highly interdependent systems
- Evaluate performance metrics as a function of system functions that can be operational, degraded, or failed
What are the research areas?
- Incorporating network and communications impacts on SoS performance
- Assessment of human performance impacts on SoS performance
- Optimization for complex SoS
- Enterprise operations analysis for large SoS
- Susceptibility assessments for complex SoS