Journal article
Robustness Elasticity in Complex Networks
PloS one, v 7(7), pp e39788-e39788
10 Jul 2012
PMID: 22808060
Abstract
Network robustness refers to a network's resilience to stress or damage. Given that most networks are inherently dynamic, with changing topology, loads, and operational states, their robustness is also likely subject to change. However, in most analyses of network structure, it is assumed that interaction among nodes has no effect on robustness. To investigate the hypothesis that network robustness is not sensitive or elastic to the level of interaction (or flow) among network nodes, this paper explores the impacts of network disruption, namely arc deletion, over a temporal sequence of observed nodal interactions for a large Internet backbone system. In particular, a mathematical programming approach is used to identify exact bounds on robustness to arc deletion for each epoch of nodal interaction. Elasticity of the identified bounds relative to the magnitude of arc deletion is assessed. Results indicate that system robustness can be highly elastic to spatial and temporal variations in nodal interactions within complex systems. Further, the presence of this elasticity provides evidence that a failure to account for nodal interaction can confound characterizations of complex networked systems.
Metrics
Details
- Title
- Robustness Elasticity in Complex Networks
- Creators
- Timothy C. Matisziw - University of MissouriTony H. Grubesic - Geographic Information Systems and Spatial Analysis Laboratory, College of Information Science and Technology, Drexel University, Philadelphia, Pennsylvania, United States of AmericaJunyu Guo - University of Missouri
- Publication Details
- PloS one, v 7(7), pp e39788-e39788
- Publisher
- Public Library Science
- Number of pages
- 10
- Grant note
- CS05 / National Academies Keck Futures Initiative 0908030; 0718091 / National Science Foundation; National Science Foundation (NSF)
- Resource Type
- Journal article
- Language
- English
- Web of Science ID
- WOS:000306355500014
- Scopus ID
- 2-s2.0-84863647205
- Other Identifier
- 991019357765704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Multidisciplinary Sciences