Abstract
This chapter reviews the network science literature in order to create a hypothesis for the recovery of infrastructure systems. We depict the cascade of infrastructure systems through networks and simulate perturbations within a singular topology and discuss how those impact multiple layers of an interconnected network. The simulation compares and contrasts the proposed recovery methods in the literature alongside true-to-life recovery, based upon case studies throughout the United States. We explore the limitations of imposing a recovery algorithm at various points in time during infrastructure failure. This chapter aims to provide resources that account for a quantitative approach to cascading infrastructure failures, as well as accounting for human nature, politics, perceptions, and communication that may prove to be hurdles to optimizing recovery.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kaplan, S., Garrick, B.J.: On the quantitative definition of risk. Risk Anal. 1, 11–27 (1981). https://doi.org/10.1111/j.1539-6924.1981.tb01350.x
International Panel on Climate Change Secretariat: AR5 Climate Change 2014: Impacts, Adaptation, and Vulnerability. International Panel on Climate Change, Geneva (2014). https://www.ipcc.ch/report/ar5/wg2/
Gomez-Baggethun, E., Ruiz-Perez, M.: Economic valuation and commodification of ecosystem services. Prog Phys Geogr. 35(5), 613–628 (2011)
Department of Homeland Security (DHS): Critical Infrastructure Sectors. United States Cyber Security and Infrastructure Security Agency. (2018). https://www.dhs.gov/cisa/critical-infrastructure-sectors
Fisher, L.: Disaster responses: more than 70 ways to show resilience. Nature. 518, 35–35 (2015). https://doi.org/10.1038/518035a
National Research Council: Disaster Resilience: A National Imperative. The National Academies Press, Washington (2012). https://doi.org/10.17226/13457
Stein, J.L., Stein, S.: Gray swans: comparison of natural and financial hazard assessment and mitigation. Nat. Hazards. 72, 1279–1297 (2014)
Lin, N., Emanuel, K.: Grey swan tropical cyclones. Nat. Clim. Chang. 6, 106–111 (2016). https://doi.org/10.1038/nclimate2777
Linkov, I., Bridges, T., Creutzig, F., et al.: Changing the resilience paradigm. Nat. Clim. Chang. 4, 407–409 (2014)
Barabasi, A., Albert, R.: Emergence of scaling in random networks. Science. 286(5439), 509–512 (1999)
Chawla, N., Ganguly, A.: Complex networks as a unified framework for descriptive analysis and predictive modeling in climate science. Stat Anal Data Min. 4(5), 497–511 (2011)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature. 393(6684), 440–442 (1998)
Clark, K., Bhatia, U., Kodra, E., Ganguly, A.R.: Resilience of the US National Airspace system airport network. IEEE Trans. Intell. Transp. Syst. 99, 1–10 (2018). Accepted (minor changes)
Bhatia, U., Kumar, D., Kodra, E., Ganguly, A.R.: Network science based quantification of resilience demonstrated on the Indian Railways Network. PLoS One. 10(11), 1–17 (2015). https://doi.org/10.1371/journal.pone.0141890
Gao, J., Barzel, B., Barabási, A.-L.: Universal Resilience Patterns in Complex Networks. Nature. 530(7590), 307–312 (2016). https://doi.org/10.1038/nature16948. Nature Publishing Group
Kinney, R., Crucitti, P., Albert, R., Latora, V.: Modeling cascading failures in the North American power grid. Eur Phys J B. 46(1), 101–107 (2005). https://doi.org/10.1140/epjb/e2005-00237-9
Newman, M.E.J.: Networks: An Introduction. Oxford University Press, Oxford (2010)
Barabasi, A., Posfai, M.: Network Science, 1st edn. University Press (2016). ISBN-10 1107076266
Christie, R.: Power systems test case archive (2000). http://www.ee.washington.edu/research/pstca/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Warner, M., Sharma, B., Bhatia, U., Ganguly, A. (2019). Evaluation of Cascading Infrastructure Failures and Optimal Recovery from a Network Science Perspective. In: Ghanbarnejad, F., Saha Roy, R., Karimi, F., Delvenne, JC., Mitra, B. (eds) Dynamics On and Of Complex Networks III. DOOCN 2017. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-14683-2_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-14683-2_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14682-5
Online ISBN: 978-3-030-14683-2
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)