Survivability and Resiliency Modeling and Analysis of an Internet of Industrial Things using Hierarchical Models

In Industry 4.0, the emergence of the Internet of industrial things (IoIT) has been a mainstream computing infrastructure for smart factories. However, IoITs show a multitude of inherent weaknesses which may restrict IoITs from fulfilling implementation expectations due to the con-figuration of the Cloud-Edge continuum. Under the needs of high-level production chain business continuity, an IoIT may be influenced by parametric or structural changes on one hand, but the system may also fail on the other. These possible events may be quantified using two metrics: survivability and resilience. This work proposes to model and evaluate a specific IoIT for survivability and resiliency quantification using a hierarchical model. The system model consists of three layers: (i) reliability block diagram (RBD) at the top level to capture the overall IoIT architecture, (ii) fault tree (FT) at the middle level to capture the configurations of subsystems, and (iii) continuous-time Markov chain (CTMC) models at the bottom level to represent the operational states of the underlying components and devices. The study can assist system managers in ensuring the maximum level of survivability and resiliency of industrial processes in smart factories by preserving operating circumstances and system configurations.