Assessing the Vulnerability of the Fiber Infrastructure to Disasters

Abstract

Abstract-Communication networks are vulnerable to natural disasters, such as earthquakes or floods, as well as to physical attacks, such as an Electromagnetic Pulse (EMP) attack. Such realworld events happen in specific geographical locations and disrupt specific parts of the network. Therefore, the geographical layout of the network determines the impact of such events on the network's connectivity. In this paper, we focus on assessing the vulnerability of (geographical) networks to such disasters. In particular, we aim to identify the most vulnerable parts of the network. That is, the locations of disasters that would have the maximum disruptive effect on the network in terms of capacity and connectivity. We consider graph models in which nodes and links are geographically located on a plane, and model the disaster event as a line segment or a circular cut. We develop algorithms that find a worstcase line segment cut and a worst-case circular cut. Then, we obtain numerical results for a specific backbone network, thereby demonstrating the applicability of our algorithms to real-world networks. Our novel approach provides a promising new direction for network design to avert geographical disasters or attacks.

The resilience of WDM networks to probabilistic geographical failures

“…Note that although these algorithms have to be executed offline in preparation for disasters, they have to consider numerous options and topologies, and therefore, efficiency is important. Moreover, our algorithms also work for the deterministic case, with superior performance compared to previous suggestions [25].…”

Robustness Comparison of 15 Real Telecommunication Networks: Structural and Centrality Measurements

“…ATTR is one when the network is fully connected; otherwise ATTR is the number of node pairs in every connected component divided by the total number of node pairs in the network. ATTR also gives the fraction of node pairs that are connected to each other [19]. At failure scenarios, the higher the average two-terminal reliability is, the higher the robustness is.…”

Resilient network design: challenges and future directions

“…Examples of factors are variations in: weather, workforce capabilities, exposure to natural disasters (e.g., earthquakes, hurricanes, ice storms, etc. ), local regulations (e.g., call before dig penalties), population density, power supply reliability and targeted malicious attacks [28]. The end result of these factors is that failures often happen in a correlated fashion with multiple near simultaneous failures.…”