Multi-Layer Graph-Based Evaluation of Space-Enabled Kill Webs

The increasing complexity and multi-domain/cross-domain integration of warfare assets suggests a need for more robust and high-performance modeling and analysis paradigms with the capability to successfully leverage such complex kill-webs. Graph Theory is an area of discrete mathematics that uses graph or “network” structures to represent objects and their relationships in a mathematical configuration. Graph Theory provides a mathematical framework for describing and analyzing complex networks for purposes such as optimization and path traversal characterization.  It has been successfully applied to areas such as transportation navigation, social networking analysis, logistics and supply chain management, and cybersecurity. In our previous Phase I effort we have demonstrated that the inherent structure of kill-webs presents an opportunity to apply proven graph theory techniques to address the USSF challenge of robustly analyzing, comparing, optimizing, and prioritizing kill-threads within the larger kill-web, and to assess the effectiveness and capability of space-based assets to improve the performance of multi-domain kill-webs. In addition to supporting comparisons between space-enabled and non-space-enabled kill-webs, our Phase I graph-based approach also supported analysis and visualization of kill-web effectiveness based on a variety of metrics, as well as identification of kill-web bottlenecks and vulnerabilities.  The principal goals of the Phase II effort are to develop an end-to-end Graph-Enabled Kill-web Optimization (GEKO) software solution to integrate SysML models and AFSIM agent-based mission scenarios with graph-based kill-web analyses and visualizations to support a variety of potential use-cases. The proposed use case applications include: (1) Real-Time Tactical Decision Support, (2) Echelon-based Situational Awareness and Decision Support, (3) Mission Simulation Analysis to Support Kill-web Optimization, (4) Kill-web Analysis to Support Acquisition Trade-Offs, and (5) Adversary Kill-web Resilience/Vulnerability Analysis. Of particular interest to the DAF/USSF are analyses that inform system design decisions to optimize the performance advantage offered by space-enabled assets as integrated into kill-webs. In pursuit of this goal, the Phase II effort will accomplish the following objectives: (1) Automated interoperability between the SysML modelling, AFSIM simulation, and GEKO analysis environments, (2) Represent kill web complexity within a graph-based architecture to support analyses of kill-web effectiveness, (3) Database of entities and mission scenarios to support representative conditions for kill-web analysis, (4) Analysis  of micro-services and browser-based visualization and reporting, and (5) Demonstrate full end-to-end GEKO capability. The attached Technical Volume will describe the scope and nature of these objectives as well as the applicable work plan and technical tasks.