Resilience and Failure Analysis in Next-Generation Communication Networks: A Contemporary Survey
This paper provides a comprehensive exploration of network resilience in next-generation (xG) cellular communication infrastructures. It begins with an introduction to the network science framework and its relevance to modern communication systems, and then delves into the theoretical foundations of network resilience, including key concepts from graph theory, complex network analysis, and cascading failure models. A detailed examination of network failures in xG networks follows, employing graph-theoretic approaches to analyze failure propagation, identify critical nodes, and assess network vulnerabilities. The paper also outlines practical methodologies for enhancing resilience, such as adaptive topology design, failure prediction, and decentralized architectural frameworks. The paper further discusses future research directions, emphasizing emerging challenges and opportunities in network resilience. It also reviews ongoing standardization efforts aimed at integrating network science principles into communication infrastructure design. Lessons learned and open challenges are summarized that require further investigation, making it a valuable resource for researchers, engineers, and practitioners seeking to advance the resilience and adaptability of xG networks.
Authors
- Siguo Bi (ORCID: https://orcid.org/0000-0001-9509-3008)
- Xin Yuan (ORCID: https://orcid.org/0000-0002-9167-1613)
- Shuyan Hu (ORCID: https://orcid.org/0000-0001-7239-211X)
- Ekram Hossain (ORCID: https://orcid.org/0000-0002-5932-6887)
- Xin Wang (ORCID: https://orcid.org/0000-0003-2292-3845)
- Kai Li (ORCID: https://orcid.org/0000-0002-0517-2392)
- Wei Ni
Institutions
- Tongji University (CN)
- Edith Cowan University (AU)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Fudan University (CN)
- UNSW Sydney (AU)
- Health Sciences and Nutrition (AU)
- Data61 (AU)
- Technische Universität Berlin (DE)
- University of Manitoba (CA)
Publication Details
- Journal
- IEEE Transactions on Network Science and Engineering
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1109/tnse.2025.3620950
- Citations
- 2
- Primary Topic
- Smart Grid Security and Resilience
- Type
- article
- Field-Weighted Citation Impact
- 2.43