On Propagation of Phenomena in Interdependent Networks

Hana Khamfroush, Novella Bartolini, Thomas F.La Porta, Ananthram Swami, Justin Dillman

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

When multiple networks are interconnected because of mutual service interdependence, propagation of phenomena across the networks is likely to occur. Depending on the type of networks and phenomenon, the propagation may be a desired effect, such as the spread of information or consensus in a social network, or an unwanted one, such as the propagation of a virus or a cascade of failures in a communication or service network. In this paper, we propose a general analytic model that captures multiple types of dependency and of interaction among nodes of interdependent networks, that may cause the propagation of phenomena. The above model is used to evaluate the effects of different diffusion models in a wide range of network topologies, including different models of random graphs and real networks. We propose a new centrality metric and compare it to more traditional approaches to assess the impact of individual network nodes in the propagation. We propose guidelines to design networks in which the diffusion is either a desired phenomenon or an unwanted one, and consequently must be fostered or prevented, respectively. We performed extensive simulations to extend our study to large networks and to show the benefits of the proposed design solutions.

Original languageEnglish (US)
Article number7542532
Pages (from-to)225-239
Number of pages15
JournalIEEE Transactions on Network Science and Engineering
Volume3
Issue number4
DOIs
StatePublished - Oct 1 2016

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Computer Networks and Communications

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