The Technical Barriers to Robust Use of Simulation
There are many obstacles for using M&S within the US DoD. This paper focuses on the technical barriers rather than the issues that relate to bureaucracy, financial resources or any other non-technical considerations. Those issues are very important and should not be overlooked, but our project, Executable Architecture Systems Engineering (EASE), is focused on technology solutions for bringing together distributed M&S for the appropriate purposes (hopefully despite many possible non-technical considerations).
The sheer breadth and depth of warfare to be represented adequately is massive. Understanding exactly what parts of warfare need to be represented is based on a detailed breakdown of the Measures of Performance (MoPs) and Measures of Effectiveness (MoEs) [3] for an event’s goals. Once the modeling requirements are known though, it is impossible to know what exactly exists throughout US DoD in order to help. There have been efforts to catalogue the existing M&S assets but the information gathered is almost always limited to textual descriptions. Much work remains to be accomplished in order to understand whether the application fits the needs per fidelity, resolution and interoperability, along with many other factors.
A major problem with using multiple systems together is the interoperability among those systems. Interoperability among distributed M&S is complex, tedious and often difficult to evaluate. Integrating models that were developed for various purposes with disparate technologies and managed by independent organizations is often the goal. The effort required to meet this goal is frequently underestimated due to misunderstood commonalities between those applications.
Common compliance with middleware architectures, modeling goals and object models gives a false impression of complete interoperability. There are numerous considerations when developing a distributed simulation environment. The event’s objectives drive the necessary simulation functions but how those simulation functions interact needs to be meticulously designed for true interoperability. The semantics of the information transmitted, the behavior necessary across multiple applications and fidelity and resolution synchronization are only a subset of the systems engineering necessary for a coherent SoS.
Once the appropriate M&S applications have been procured, configured and integrated, there is a significant workforce requirement to learn how to use, setup, manage and execute the M&S applications for both the current event as well as future events. Reuse of M&S environments can provide cost avoidance, but retaining organizational knowledge is difficult with workforce turnover, particularly in this era of smaller budgets and shorter execution time periods. Once a M&S event concludes, we have often seen computers repurposed, configurations and software modifications completely lost and engineers moved on to other projects. It becomes impossible to build on the previous event with small changes so the organization must start almost from the beginning spending nearly the same resources as spent originally.
Towards this end, we have established a data-driven systems engineering infrastructure which allows SoS design encapsulation and connected an interview subsystem which allows a user to launch a distributed M&S execution based on functional and scenario choices. We have implemented generative programming techniques [4], which automatically generate executable computer programming artifacts from a higher level source, in order to quickly deploy a SoS architecture for military analysis. The flexibility required to implement our goal requires systems architecture qualities and objectives. This includes encapsulation of functionality into appropriately sized portions to be able to manipulate and construct larger capabilities, as needed, with as little engineering effort as possible. We aim towards an architecture that is fully compliant with US Army Verification and Validation guidance [5], and robust enough for decisionoriented analysis, while maintaining flexibility and quickness in order to save the DoD tremendous amounts of time and effort when constructing distributed M&S environments for various uses.