Greedy optimization of resistance-based graph robustness with global and local edge insertions

The total effective resistance, also called the Kirchhoff index, provides a robustness measure for a graph G. We consider two optimization problems of adding k new edges to G such that the resulting graph has minimal total effective resistance (i.e., is most robust)—one where the new edges can be anywhere in the graph and one where the new...

Topological Approach to Measure the Recoverability of Optical Networks

Optical networks are vulnerable to failures due to targeted attacks or large-scale disasters. The recoverability of optical networks refers to the ability of an optical network to return to a desired performance level after suffering topological perturbations such as link failures. This paper proposes a general topological approach and...

Reachability-based Robustness of Controllability in Sparse Communication Networks

In this paper, we propose closed-form analytic approximations for the number of controllable nodes in sparse communication networks from the aspect of network controllability, considering link-based random attack, targeted attack, as well as random attack under the protection of critical links. We compare our approximations with simulation...

Using Machine Learning to Quantify the Robustness of Network Controllability

This paper presents machine learning based approximations for the minimum number of driver nodes needed for structural controllability of networks under link-based random and targeted attacks. We compare our approximations with existing analytical approximations and show that our machine learning based approximations significantly outperform...

Quantifying the Robustness of Network Controllability

In this paper, we propose closed-form analytic approximations for the minimum number of driver nodes needed to fully control networks, where links are removed according to both random and targeted attacks. Our approximations rely on the concept of critical links. A link is called critical if its removal increases the required number of driver...

Inconsistencies Among Spectral Robustness Metrics

Network robustness plays a critical role in the proper functioning of modern society. It is common practice to use spectral metrics, to quantify the robustness of networks. In this paper we compare eight different spectral metrics that quantify network robustness. Four of the metrics are derived from the adjacency matrix, the others follow...

On generalized windmill graphs

In this paper we will consider generalizations of the class of so-called windmill graphs, which were recently introduced by Estrada [6]. A windmill graph W(η,k) consists of η copies of the complete graph Kk, with every node connected to a common node. Estrada [6] showed that the clustering coefficient and the transitivity index of windmill...

Enhanced interconnection model in geographically interdependent networks

Interconnection between telecommunication networks and other critical infrastructures is usually established through nodes that are spatially close, generating a geographical interdependency. Previous work has shown that in general, geographically interdependent networks are more robust with respect to cascading failures when the...

A New Metric for Robustness with Respect to Virus Spread (Work in Progress)

The robustness of a network is depending on the type of attack we are considering. In this paper we focus on the spread of viruses on networks. It is common practice to use the epidemic threshold as a measure for robustness. Because the epidemic threshold is inversely proportional to the largest eigenvalue of the adjacency matrix, it seems easy...

ELASTICITY: Topological Characterization of Robustness in Complex Networks