WRT-1027: Ecology-Inspired Techniques for Resilient Design of Systems of Systems
Report Number: SERC-2021-TR-019
Publication Date: 2022-03-29
Project: New Project Incubator 2019-2020
Ecology-Inspired Techniques for Resilient Design of Systems of Systems (SoS)
Dr. Richard Malak Jr.
This research investigates the use of Ecological Network Analysis (ENA) to evaluate engineered SoS resilience and support Systems of Systems Engineering (SoSE) decisions. The work focuses specifically on the Degree of System Order (DoSO) metric and the Window of Vitality (WoV) concept from the ENA literature and its potential application in SoSE. The project entails computational studies to validate the ENA-based metrics and demonstrate SoSE decision-making using these metrics. SoS architectures are modeled and evaluated for resilience to a range of disruptions using traditional metrics (capturing initial loss, recovered performance, etc.) and the proposed ENA-based metrics. These studies highlighted key relationships in the SoS resilience vs. affordability trade space and identified promising pathways for resilient SoS design using these ENA-based metrics.
The research also develops an extended ENA framework and modified metrics that enable ecology-inspired design and analysis of SoS with multiple distinct but inter-dependent interactions, such as critical cyber-physical infrastructure. This analysis framework is capable of identifying architectures where the lack of adaptability in the cyber interactions leaves the SoS vulnerable to cascading failures in the physical infrastructure and is especially relevant with the increasing threat of cyber disruptions. Application of the extended framework is demonstrated using a design space exploration study of two synthetic critical infrastructure case studies: (a) pipeline distribution networks, and (b) power grids. These case studies were chosen because they are examples of critical infrastructure and their resilience is of great importance. The application to these case studies validated that the developed framework can account for both topological/physical and behavioral/functional features of SoS architectures. Finally, a prototype decision support tool for SoS design using ENA is implemented and demonstrated. The prototype tool focuses on implementing novel functionality stemming from the ENA-based metrics, such as filtering poorly-rated SoS.