A network tool to analyse and improve robustness of system architectures

Abstract

The architecture of a system is decided at the initial stage of the design. However, the robustness of the system is not usually assessed in detail during the initial stages, and the exploration of alternative system architectures is limited due to the influence of previous designs and opinions. This article presents a novel network generator that enables the analysis of the robustness of alternative system architectures in the initial stages of design. The generator is proposed as a network tool for system architectures dictated by their configuration of source and sink components structured in a way to deliver a particular functionality. Its parameters allow exploration with theoretical patterns to define the main structure and hub structure, vary the number, size, and connectivity of hub components, define source and sink components and directionality at the hub level and adapt a redundancy threshold criterion. The methodology in this article assesses the system architecture patterns through robustness and modularity network based metrics and methods. Two naval distributed engineering system architectures are examined as the basis of reference for the simulated networks. The generator provides the capacity to create alternative complex system architecture options with identifiable patterns and key features, aiding in a broader explorative and analytical, in-depth, time and cost-efficient initial design process.

Robust design of complex socio-technical systems against seasonal effects: a network motif-based approach

“…This model was successfully applied to public transport systems. In another study, Paparistodimou et al (2020) proposed a network generator to support system architectures' robustness analysis in the initial design stages. Focusing on design process robustness, Piccolo, Lehmann, & Maier (2018) presented a bipartite network-based method to investigate the interplay between people and the design activities and its impact on the robustness of design progress.…”

Characterizing Systems Of Systems Change And Failure Via Network-based Metrics

“…For instance, Antul et al, (2017) represents an SoS as the network of its CSs and measures the algebraic connectivity to capture "a network's vulnerability to disconnection (e.g., removal of a CSs)." In a similar fashion, the robustness coefficient has been used in the literature (Haley et al, 2016;Paparistodimou, Duffy, Whitfield, Knight, & Robb, 2020;Walsh et al, 2019) and characterizes the largest connected component (connected nodes) after a node removal (e.g., removal of a CS in an SoS or the loss of a function). Paparistodimou et al, (2020) use the robustness coefficient to compare naval distributed engineering system architectures options.…”

“…In a similar fashion, the robustness coefficient has been used in the literature (Haley et al, 2016;Paparistodimou, Duffy, Whitfield, Knight, & Robb, 2020;Walsh et al, 2019) and characterizes the largest connected component (connected nodes) after a node removal (e.g., removal of a CS in an SoS or the loss of a function). Paparistodimou et al, (2020) use the robustness coefficient to compare naval distributed engineering system architectures options. Walsh et al, (2019) use the robustness coefficient to explore the correlation between robustness and modularity.…”

Robustness of decentralized decision‐making architectures in command and control systems

“…A system's architecture is thought to exert significant influence on its “‐ility” characteristics throughout its life span 22,23 . More decentralized architectural patterns have been linked to ‐ility outcomes like robustness and other closely related constructs including flexibility, adaptability, and others 11,24–27 . While most C2 studies have not sought to explicitly link decentralization to performance robustness, robustness has been observed as an emergent property of many fielded C2 architectures (but not necessarily an outcome of deliberate design decisions) 5 .…”

“…22,23 More decentralized architectural patterns have been linked to -ility outcomes like robustness and other closely related constructs including flexibility, adaptability, and others. 11,[24][25][26][27] While most C2 studies have not sought to explicitly link decentralization to performance robustness, robustness has been observed as an emergent property of many fielded C2 architectures (but not necessarily an outcome of deliberate design decisions). 5 In this study, using an inherently hierarchical military C2 system, we seek to explore the influence of decentralized decision-making on the system's performance robustness.…”