Analysis and modeling of critical networks and dependencies within the urban area

Kurzfassung

Critical infrastructures are the backbone of modern society, providing essential services and systems enabling people to live and work. Therefore, it is crucial to ensure their reliability, security, and resilience to protect the population’s well-being and ensure the continuity of social and economic activities. Critical infrastructures encompass essential services such as electricity and water supply. These infrastructures are interdependent, so a malfunction or interruption of one infrastructure can impact other infrastructures. Understanding these dependencies is essential to ensure infrastructure resilience and security. Despite the increasing interconnections between these infrastructures, comprehensive data on their interactions and dependencies is lacking. Additionally, the available data from different infrastructures are often heterogeneous. Furthermore, there aren’t methods to adequately identify and analyze the dependencies between different infrastructures. The goal of this study is to propose a graph-based dependency model for critical infrastructures, addressing the issues mentioned above. Within this specific model, a clear differentiation between critical infrastructure entities providing and consuming services is established. The impact of dependencies on entities consuming services is articulated through a relationship between the dependent entities. Furthermore, a method for extracting dependencies is proposed, enabling the identification of physical dependencies through analyzing topological data of infrastructures. In addition, a simulation environment integrating the proposed dependency model and dependency extraction is presented. Its primary purpose is to perform scenario simulations within a hypothetical urban environment. For evaluation purposes, a simulation-based experiment with a total of 1198 simulated critical infrastructure entities was conducted. This experiment demonstrated the proposed model’s and the simulation environment’s capabilities in considering dependencies between the urban water and electricity infrastructures. The infrastructures were visualized, and the simulation results were provided in a uniform data format for the infrastructure stakeholders. Furthermore, a performance evaluation was conducted based on the simulation-experiments data to assess the execution times of the implemented approaches. The results of this performance evaluation show that the implementation of the dependency model is efficient in terms of execution time compared to the domain simulators utilized in the examination. For the electricity infrastructure, the implemented concepts for the dependency analysis require 15 percent of the electricity simulator’s execution time. For the water simulator, it is only 1.82 percent. The results of this work demonstrate the potential of the presented graph-based dependency model and simulation environment for analyzing, extracting, simulating, and visualizing dependencies between critical infrastructures. Moreover, the approach could help to improve critical infrastructures ‘resilience and security by providing a simulation environment for infrastructure stakeholders. Lastly, this work’s model and simulation environment are designed to be expandable, allowing the inclusion of additional critical infrastructures in the future.