Repository logo
 

Critical link analysis of a national internet backbone via dynamic perturbation

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Herrera, M 
Pérez-Hernández, M 
Jain, AK 
Parlikad, AK 

Abstract

Long-haul backbone communication networks provide internet services across a region or a country. The access to internet at smaller areas and the functioning of other critical infrastructures rely on the long-haul backbone high speed services and resilience. Hence, such networks are key for the decision-making of internet service managers and providers, as well as for the management and control of other critical infrastructures. This paper proposes a critical link analysis of the physical infrastructure of the UK internet backbone network from a dynamic, complex network approach. To this end, perturbation network analyses provide a natural framework to measure the network tolerance facing structural or topological modifications. Furthermore, there have been taken into account variations on data-traffic for the internet backbone that usually happen in a typical day. The novelty of the proposal is, then, twofold: proposing a weighted (traffic informed) Laplacian matrix to compute a perturbation centrality measure, and enhancing it by a time-dependent perturbation analysis to detect changes in link criticality within the network, coming from data traffic variation in a day. The results show which are the most critical links at every time of the day, being of main importance for protection, maintenance and mitigation plans for the UK internet backbone.

Description

Keywords

Communication network, perturbation analysis, graph theory, complex networks, dynamic systems

Journal Title

IFAC-PapersOnLine

Conference Name

Advanced Maintenance Engineering, Services and Technologies

Journal ISSN

2405-8963
2405-8963

Volume Title

53

Publisher

Elsevier BV

Rights

All rights reserved
Sponsorship
Engineering and Physical Sciences Research Council (EP/R004935/1)
EPSRC (via Lancaster University) (Unknown)
This research was supported by the Next Generation Converged Digital Infrastructure project (EP/R004935/1) funded by the Engineering and Physical Sciences Research Council and BT.