Exploring a Timed-automata Fuzzy Cognitive Maps Based Approach for Modeling Systems of Systems☆

Abstract The need for effectively developing high quality solutions for very large scale, complex problems continues to drive research in modeling and analyzing System of Systems (SoS). These kinds of systems span numerous domains, including essential infrastructure (water, power, transportation, emergency response, healthcare, education, finance, military, environmental protection etc.). A SoS is composed of independent, autonomous constituent systems; the SoS provides emergent behavior that goes beyond the capabilities of its constituent systems. Having the capability to predict the emergent behavior would be very valuable in assessing the impact of changes in a constituent system's behavior on the emergent behavior of the SoS. For example, if a constituent system is being added, modified, or retired, how will this impact the SoS? In this paper, we explore a new approach to model a SoS, with a focus on emergent behavior for non-functional properties (e.g., safety, reliability etc.,). The approach is based on the visual, formal method Timed-Automata-Based Fuzzy Cognitive Maps (TA-FCMs). A published case study on a water treatment SoS for the Beijing Nanshahe River Basin is used in this work. In future work, we plan to refine our modeling approach and continue on with investigating approach to provide the predictive analysis and formal verification.