Connectivity in Interdependent Networks

TL;DR

This paper introduces a graph model for interdependent networks, analyzing their connectivity and proposing algorithms to evaluate and enhance supply node connectivity, which is crucial for the robustness of cyber-physical systems.

Contribution

It presents a novel model for interdependent networks, algorithms for evaluating and maximizing supply node connectivity, and theoretical guarantees for random assignment methods.

Findings

Algorithms effectively evaluate supply node connectivity.

Random assignment achieves near-optimal connectivity in most cases.

The model applies to cyber-physical and layered network systems.

Abstract

We propose and analyze a graph model to study the connectivity of interdependent networks. Two interdependent networks of arbitrary topologies are modeled as two graphs, where every node in one graph is supported by supply nodes in the other graph, and a node fails if all of its supply nodes fail. Such interdependence arises in cyber-physical systems and layered network architectures. We study the \emph{supply node connectivity} of a network: namely, the minimum number of supply node removals that would disconnect the network. We develop algorithms to evaluate the supply node connectivity given arbitrary network topologies and interdependence between two networks. Moreover, we develop interdependence assignment algorithms that maximize the supply node connectivity. We prove that a random assignment algorithm yields a supply node connectivity within a constant factor from the optimal for most networks.