2020IEEE AccessOpen access

The Robustness of Interdependent Networks With Traffic Loads and Dependency Groups

Lin Zhou, Xiaogang Qi, Lifang Liu

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Abstract

Existing researches on cascading failures of interdependent networks are mainly based on the percolation theory and do not consider the influence of dynamic load propagation and dependency groups. In this paper, we develop a novel interdependent system model to capture this phenomenon, also known as the hybrid cascading failure model. A degree-based targeted attack strategy on the cascading failure process of interdependent networks is studied. Combining dependency groups, interdependent relations, and traffic loads, small fraction of initial failed nodes may lead to the complete fragmentation of interdependent networks. The influence of two different dependency groups distributions on the robustness of interdependent networks under three coupling preferences is studied respectively. We provide a thorough analysis of the dynamics of cascading failures in interdependent networks initiated with a targeted attack. The system robustness is quantified as the surviving fraction of nodes in the giant connected component at the end of cascading failures. Our results highlight the need to consider loads, group effects and coupling preferences when designing the robust interdependent networks. And it is necessary to take steps in the early stage to reduce the losses caused by the large-scale cascading failures of infrastructure networks.

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Existing researches on cascading failures of interdependent networks are mainly based on the percolation theory and do not consider the influence of dynamic load propagation and dependency groups. In this paper, we develop a novel interdependent system model to capture this phenomenon, also known as the hybrid cascading failure model. A degree-based targeted attack strategy on the cascading failure process of interdependent networks is studied. Combining dependency groups, interdependent relations, and traffic loads, small fraction of initial failed nodes may lead to the complete fragmentation of interdependent networks. The influence of two different dependency groups distributions on the robustness of interdependent networks under three coupling preferences is studied respectively. We provide a thorough analysis of the dynamics of cascading failures in interdependent networks initiated with a targeted attack. The system robustness is quantified as the surviving fraction of nodes in the giant connected component at the end of cascading failures. Our results highlight the need to consider loads, group effects and coupling preferences when designing the robust interdependent networks. And it is necessary to take steps in the early stage to reduce the losses caused by the large-scale cascading failures of infrastructure networks.

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Available abstract

Existing researches on cascading failures of interdependent networks are mainly based on the percolation theory and do not consider the influence of dynamic load propagation and dependency groups. In this paper, we develop a novel interdependent system model to capture this phenomenon, also known as the hybrid cascading failure model. A degree-based targeted attack strategy on the cascading failure process of interdependent networks is studied. Combining dependency groups, interdependent relations, and traffic loads, small fraction of initial failed nodes may lead to the complete fragmentation of interdependent networks. The influence of two different dependency groups distributions on the robustness of interdependent networks under three coupling preferences is studied respectively. We provide a thorough analysis of the dynamics of cascading failures in interdependent networks initiated with a targeted attack. The system robustness is quantified as the surviving fraction of nodes in the giant connected component at the end of cascading failures. Our results highlight the need to consider loads, group effects and coupling preferences when designing the robust interdependent networks. And it is necessary to take steps in the early stage to reduce the losses caused by the large-scale cascading failures of infrastructure networks.

Key concepts: Robustness (evolution), Computer science, Dependency (UML), Interdependence, Interdependent networks, Distributed computing, Computer network, Computer security

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