A Complex Network Framework for Validated Assessments of Systems of Systems Robustness

Abstract

The complexity of modern systems of systems (SoS) requires the ability to quickly and effectively evaluate robustness in architecture alternatives. This article presents a framework for rapid, quantitative comparisons of robustness in SoS architectures that leverages complex network methods for assessing robustness and design of experiments (DoE) techniques for validating their use in the scenario of interest. We consider both single-layer and multilayer network representations of SoS and focus on algebraic connectivity, inverse average path length, and largest connected component size as measures of robustness. Two case studies are used to illustrate our framework and assess its utility: a command, control, communications, computer, intelligence, surveillance, and reconnaissance (C4ISR) simulation and a multilayer message-passing network simulation. We find that most of the considered network metrics capture expected robustness trends, though their ability to capture these trends is often affected by the scenario of interest. These results demonstrate the potential value of complex network methods for lightweight analysis of robustness in SoS architecture alternatives, when appropriately supported by DoE methods for understanding their limitations.