Cascading failures on interdependent networks with star dependent links

Tianqiao Zhang, Yang Zhang, Xuzhen Zhu and Junliang Chen

Physica A: Statistical Mechanics and its Applications, 2019, vol. 535, issue C

Abstract: In this paper, we propose a cascading failure model with star interdependent links. To describe the model theoretically, a generalized percolation theory is developed. Through extensive numerical simulations and theoretical analyses, we study the phase transition of the system on artificial networks. On both ER-ER and SF-SF networks, the system exhibits a continuous (discontinuous) phase transition for small (large) fraction of service nodes. On ER-ER networks, the more service links of a service node, the system is more likely to exhibit a discontinuous phase transition. On SF-SF networks, the service links of a service node cannot alter the phase of the system. Our suggested theory agrees well with the numerical simulations.

Keywords: Interdependent networks; Percolation theory; Phase transition (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119312889
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119312889

DOI: 10.1016/j.physa.2019.122222

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().