Design of survivable wireless backhaul networks with reliability considerations

Raayatpanah, Mohammad Ali; Beheshtkhah, Mahdi Kabiri; Eshghi, Farshad; Kelarestaghi, Manoochehr; Nepomuceno, Napoleão

doi:10.1016/j.cor.2022.106120

Cited by 1 publication

(1 citation statement)

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“…Raayatpanah et al [36] presented a design for survivable wireless backhaul networks, optimizing network design by considering the probability of link failures and the importance of nodes. Simulation experiments demonstrated the model's effectiveness in improving network survivability, but dynamic network conditions and different failure types were not considered.…”

Section: Related Workmentioning

confidence: 99%

ENRN: A System for Evaluating Network Resilience against Natural Disasters

Alenazi

2023

Mathematics

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The frequency and severity of natural disasters is surging, posing an urgent need for robust communication network infrastructure that is capable of withstanding these events. In this paper, we present a groundbreaking graph-theoretic system designed to evaluate and enhance network resilience in the face of natural disasters. Our solution harnesses the power of topological robustness metrics, integrating real-time weather data, geographic information, detailed network topology data, advanced resilience algorithms, and continuous network monitoring. The proposed scheme considers four major real-world U.S.-based network providers and evaluates their physical topologies against two major hurricanes. Our novel framework quantifies the important characteristics of network infrastructure; for instance, AT&T is identified to have fared better against Hurricane Ivan (57.98 points) than Hurricane Katrina (39.17 points). We not only provide current insights into network infrastructure resilience, but also uncover valuable findings that shed light on the performance of backbone U.S. networks during hurricanes. Furthermore, our findings provide actionable insights to enrich the overall survivability and functionality of communication networks, mitigating the adverse impacts of natural disasters on communication systems and critical services in terms of improving network resiliency via adding additional nodes and link or rewiring.

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Section: Related Workmentioning

confidence: 99%

ENRN: A System for Evaluating Network Resilience against Natural Disasters

Alenazi

2023

Mathematics

View full text Add to dashboard Cite

show abstract

Design of survivable wireless backhaul networks with reliability considerations

Cited by 1 publication

References 47 publications

ENRN: A System for Evaluating Network Resilience against Natural Disasters

ENRN: A System for Evaluating Network Resilience against Natural Disasters

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