Restoration of interdependent network against cascading overload failure

Zhong, Jilong; Zhang, Fengming; Yang, Shunkun; Li, Daqing

doi:10.1016/j.physa.2018.09.130

Cited by 43 publications

(15 citation statements)

References 28 publications

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“…Ouyang and Dueñas-Osorio 2011 [23] examined different strategies for designing the interfaces between different infrastructure systems in an effort to maximize resistance to random natural disaster scenarios, Ouyang and Wang 2015 [24] examined different interdependent network restoration strategies, and Ouyang 2017 [22] examined worst-case scenarios as the results of directed attacks. Zhong et al 2019 [31] studied the repair process of various interdependent networks with load-dependent cascading failures.…”

Section: Introductionmentioning

confidence: 99%

A linear input dependence model for interdependent networks

Kaul,

Rumpf

2021

Preprint

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We consider a linear relaxation of a generalized minimum-cost network flow problem with binary input dependencies. In this model the flows through certain arcs are bounded by linear (or more generally, piecewise linear concave) functions of the flows through other arcs. This formulation can be used to model interrelated systems in which the components of one system require the delivery of material from another system in order to function (for example, components of a subway system may require delivery of electrical power from a separate system). We propose and study randomized rounding schemes for how this model can be used to approximate solutions to a related mixed integer linear program for modeling binary input dependencies. The introduction of side constraints prevents this problem from being solved using the well-known network simplex algorithm, however by characterizing its basis structure we develop a generalization of network simplex algorithm that can be used for its efficient solution.

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Section: Introductionmentioning

confidence: 99%

A linear input dependence model for interdependent networks

Kaul,

Rumpf

2021

Preprint

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“…Considering the directionality of the real network, Liu and Stanley developed a theoretical framework based on the generation function and percolation theory and found that for different network models, the correlations between the in-degree and out-degree brings different results 28 . Based on a load-dependent cascading model, Zhong and Zhang simulated cascading failures when considering recovery strategies against, for different coupling strength and network topologies in interdependent networks 27 , In this paper, the overload status of the node is also considered, but only a value is set for it, and there is a lack of discussion about the redistribution of overload. As can be seen from the above literature, most researchers of them rarely consider the case of edges in the networks with redundancy capability when building the model of cascade failure, but in a real network, many connected edges often have some redundancy capabilities.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear model of cascade failure in weighted complex networks considering overloaded edges

Chen

Zhao

Gao

et al. 2020

Sci Rep

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Considering the elasticity of the real networks, the components in the network have a redundant capacity against the load, such as power grids, traffic networks and so on. Moreover, the interaction strength between nodes is often different. This paper proposes a novel nonlinear model of cascade failure in weighted complex networks considering overloaded edges to describe the redundant capacity for edges and capture the interaction strength of nodes. We fill this gap by studying a nonlinear weighted model of cascade failure with overloaded edges over synthetic and real weighted networks. The cascading failure model is constructed for the first time according to the overload coefficient, capacity parameter, weight coefficient, and distribution coefficient. Then through theoretical analysis, the conditions for stopping failure cascades are obtained, and the analysis shows the superiority of the constructed model. Finally, the cascading invulnerability is simulated in several typical network models and the US power grid. The results show that the model is a feasible and reasonable change of weight parameters, capacity coefficient, distribution coefficient, and overload coefficient can significantly improve the destructiveness of complex networks against cascade failure. Our methodology provides an efficacious reference for the control and prevention of cascading failures in many real networks.

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“…Jianwei Wang et al proposed a cascading model to explain the attack vulnerability of scale-free networks [30]. Propagation of cascading failures [31], [32] and restoration from cascading failure [33]- [36] has been studied. After [29], a series of studies about attack tolerance or vulnerability of static networks [37]- [41] and temporal networks [42]- [47] emerged.…”

Section: Introductionmentioning

confidence: 99%

A Complex Networks Approach for Reliability Evaluation of Swarm Systems Under Malicious Attacks

et al. 2020

Self Cite

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The reliability of swarm systems needs to be investigated because of their self-adaption and self-organized features. Previous studies mainly focused on the reliability of a single agent, whereas for swarm systems, the ability to maintain their overall connection and function under adverse conditions is more important. It remains challenging on how to evaluate the reliability of swarm systems at the system level. In this paper, we present a reliability evaluation method for swarm systems by characterizing the behavior of the whole system using the method of temporal network analysis. A novel comprehensive reliability metric, i.e. cooperation reliability (CR), is proposed, considering both system integrity and motion consensus. Meanwhile, by identifying critical individuals in swarm systems, we design different malicious attack strategies. It is found that the malicious attacks perform much more harmfully to the reliability of swarm systems than noise and random attack. Moreover, we find that the reliability of a swarm system is sensitive to the swarm density in our framework due to the dynamical interaction of the system. Our findings may shed light on understanding the complicated behaviors of swarm systems under attack and designing a more robust swarm system.

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Restoration of interdependent network against cascading overload failure

Cited by 43 publications

References 28 publications

A linear input dependence model for interdependent networks

A linear input dependence model for interdependent networks

Nonlinear model of cascade failure in weighted complex networks considering overloaded edges

A Complex Networks Approach for Reliability Evaluation of Swarm Systems Under Malicious Attacks

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