Cluster damage robustness analysis and space independent community detection in complex networks
type: CreativeWork
description: This thesis investigates the evolution of two very different complex systems using network theory. This multi-disciplinary technique is widely used to model and analyse vastly diverse systems of multiple interacting components, and therefore, it is applied in this thesis to study the complexity of the systems. This complexity is rooted in the components’ interactions such that the whole system is more than the sum of all the individual parts. The first novelty in this research is the proposal of a new type of structural perturbation, cluster damage, for measuring another dimension of network robustness. The second novelty is the first application of a community detection method, which uncovers space-independent communities in spatial networks, to airport and linguistic networks. A critical property of complex systems – robustness – is explored within a partial model of the Internet, by demonstrating a novel perturbation strategy based on the iterative removal of clusters. The main contribution of this theoretical case study is the methodology for cluster damage, which has not been investigated by literature on the robustness of complex networks. The model, part of the Internet at the Autonomous System level, only serves as a domain where the novel methodology is demonstrated, and it is chosen because the Internet is known to be robust due to its distributed (non-centralised) nature, even though it is often subjected to large perturbations and failures. The first applied case study is in the field of air transportation. Specifically, it explores the topology and passenger flows of the United States Airport Network (USAN) over two decades. The network model consists of a time-series of six network snapshots for the years 1990, 2000 and 2010, which capture bi-monthly passenger flows among US airports. Since the network is embedded in space, the volume of these flows is naturally affected by spatial proximity, and therefore, a model (recently proposed in the literature)…
abstract: This thesis investigates the evolution of two very different complex systems using network theory. This multi-disciplinary technique is widely used to model and analyse vastly diverse systems of multiple interacting components, and therefore, it is applied in this thesis to study the complexity of the systems. This complexity is rooted in the components’ interactions such that the whole system is more than the sum of all the individual parts. The first novelty in this research is the proposal of a new type of structural perturbation, cluster damage, for measuring another dimension of network robustness. The second novelty is the first application of a community detection method, which uncovers space-independent communities in spatial networks, to airport and linguistic networks. A critical property of complex systems – robustness – is explored within a partial model of the Internet, by demonstrating a novel perturbation strategy based on the iterative removal of clusters. The main contribution of this theoretical case study is the methodology for cluster damage, which has not been investigated by literature on the robustness of complex networks. The model, part of the Internet at the Autonomous System level, only serves as a domain where the novel methodology is demonstrated, and it is chosen because the Internet is known to be robust due to its distributed (non-centralised) nature, even though it is often subjected to large perturbations and failures. The first applied case study is in the field of air transportation. Specifically, it explores the topology and passenger flows of the United States Airport Network (USAN) over two decades. The network model consists of a time-series of six network snapshots for the years 1990, 2000 and 2010, which capture bi-monthly passenger flows among US airports. Since the network is embedded in space, the volume of these flows is naturally affected by spatial proximity, and therefore, a model (recently proposed in the literature)…
author: Gegov, Emil
language: en
keywords: Air transportation, Language acquisition, Internet
date published: 2012
date modified: 2026-07-24T01:23:28Z
provider: University of Brunel
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Brunel University School of Engineering and Design PhD Theses