Cascading failures with local load redistribution in interdependent Watts–Strogatz networks
Chen Hong (),
Jun Zhang (),
Wen-Bo Du,
Jose M Sallan and
Oriol Lordan
Additional contact information
Chen Hong: School of Electronic and Information Engineering, Beihang University, Beijing 100191, P. R. China
Jun Zhang: School of Electronic and Information Engineering, Beihang University, Beijing 100191, P. R. China
Wen-Bo Du: School of Electronic and Information Engineering, Beihang University, Beijing 100191, P. R. China
Oriol Lordan: Universitat Politècnica de Catalunya-BarcelonaTech, C/Colom no. 11, Terrassa 08222, Spain
International Journal of Modern Physics C (IJMPC), 2016, vol. 27, issue 11, 1-10
Abstract:
Cascading failures of loads in isolated networks have been studied extensively over the last decade. Since 2010, such research has extended to interdependent networks. In this paper, we study cascading failures with local load redistribution in interdependent Watts–Strogatz (WS) networks. The effects of rewiring probability and coupling strength on the resilience of interdependent WS networks have been extensively investigated. It has been found that, for small values of the tolerance parameter, interdependent networks are more vulnerable as rewiring probability increases. For larger values of the tolerance parameter, the robustness of interdependent networks firstly decreases and then increases as rewiring probability increases. Coupling strength has a different impact on robustness. For low values of coupling strength, the resilience of interdependent networks decreases with the increment of the coupling strength until it reaches a certain threshold value. For values of coupling strength above this threshold, the opposite effect is observed. Our results are helpful to understand and design resilient interdependent networks.
Keywords: Cascading failures; Watts–Strogatz network; interdependent networks (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)
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DOI: 10.1142/S012918311650131X
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