Community detection and resilience in multi-source, multi-terminal networks

Author:

Rocco Claudio M1,Barker Kash2,Moronta Jose3,Ramirez-Marquez Jose E45ORCID

Affiliation:

1. Facultad de Ingeniería, Universidad Central de Venezuela, Caracas, Venezuela

2. School of Industrial & Systems Engineering, The University of Oklahoma, Norman, OK, USA

3. Departamento de Tecnología Industrial, Universidad Simón Bolívar, Caracas, Venezuela

4. School of Systems & Enterprises, Stevens Institute of Technology, Hoboken, NJ, USA

5. School of Sciences and Engineering, Tecnologico de Monterrey, Zapopan, México

Abstract

Many networks, particularly infrastructure networks, have multiple source nodes and multiple terminal nodes. And many such networks exhibit community structures, wherein the network is partitioned into groups of densely connected nodes with sparse connections between groups, based on topology or spatial characteristics, among others. This article proposes an approach for evaluating the effects of disruptive events, or the disconnection of network components due to failures or attacks, to the community structures and to the total network. The approach enables the assessment of resilience, evaluating both the vulnerability of the network and the recoverability enabled by different network restoration sequences. Different predefined restoration sequences are compared from different perspectives, including cost and strategy characteristics as well as resilience objectives (partial or complete restoration). The approach is illustrated with the topology of an electric power network.

Funder

Division of Civil, Mechanical and Manufacturing Innovation

Publisher

SAGE Publications

Subject

Safety, Risk, Reliability and Quality

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1. Optimal allocation of financial resources for ensuring reliable resilience in binary-state network infrastructure;Reliability Engineering & System Safety;2024-10

2. Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems;Reliability Engineering & System Safety;2023-07

3. A Fairness-Based Approach to Network Restoration;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2023-06

4. Community structure recovery optimization for partial disruption, functionality, and restoration in interdependent networks;Reliability Engineering & System Safety;2023-01

5. Disruption-Robust Community Detection Using Consensus Clustering in Complex Networks;2022 IEEE International Symposium on Technologies for Homeland Security (HST);2022-11-14

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