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Cascading network failure

Yosef Kornbluth, Gilad Barach, Yaakov Tuchman, Benjamin Kadish, Gabriel Cwilich, Sergey V Buldyrev
We study the cascading failure of networks due to overload, using the betweenness centrality of a node as the measure of its load following the Motter and Lai model. We study the fraction of survived nodes at the end of the cascade p_{f} as a function of the strength of the initial attack, measured by the fraction of nodes p that survive the initial attack for different values of tolerance α in random regular and Erdös-Renyi graphs. We find the existence of a first-order phase-transition line p_{t}(α) on a p-α plane, such that if p<p_{t}, the cascade of failures leads to a very small fraction of survived nodes p_{f} and the giant component of the network disappears, while for p>p_{t}, p_{f} is large and the giant component of the network is still present...
May 2018: Physical Review. E
WenJie Kang, Gang Hu, PeiDong Zhu, Qiang Liu, Zhi Hang, Xin Liu
Many previous works only focused on the cascading failure of global coupling of one-to-one structures in interdependent networks, but the local coupling of dual coupling structures has rarely been studied due to its complex structure. This will result in a serious consequence that many conclusions of the one-to-one structure may be incorrect in the dual coupling network and do not apply to the smart grid. Therefore, it is very necessary to subdivide the dual coupling link into a top-down coupling link and a bottom-up coupling link in order to study their influence on network robustness by combining with different coupling modes...
May 24, 2018: Sensors
Benjamin Schäfer, Dirk Witthaut, Marc Timme, Vito Latora
Reliable functioning of infrastructure networks is essential for our modern society. Cascading failures are the cause of most large-scale network outages. Although cascading failures often exhibit dynamical transients, the modeling of cascades has so far mainly focused on the analysis of sequences of steady states. In this article, we focus on electrical transmission networks and introduce a framework that takes into account both the event-based nature of cascades and the essentials of the network dynamics...
May 17, 2018: Nature Communications
Malbor Asllani, Timoteo Carletti
The network of interactions in complex systems strongly influences their resilience and the system capability to resist external perturbations or structural damages and to promptly recover thereafter. The phenomenon manifests itself in different domains, e.g., parasitic species invasion in ecosystems or cascade failures in human-made networks. Understanding the topological features of the networks that affect the resilience phenomenon remains a challenging goal for the design of robust complex systems. We hereby introduce the concept of non-normal networks, namely networks whose adjacency matrices are non-normal, propose a generating model, and show that such a feature can drastically change the global dynamics through an amplification of the system response to exogenous disturbances and eventually impact the system resilience...
April 2018: Physical Review. E
Chen Chen, Jingrui He, Nadya Bliss, Hanghang Tong
Networks are prevalent in many high impact domains. Moreover, cross-domain interactions are frequently observed in many applications, which naturally form the dependencies between different networks. Such kind of highly coupled network systems are referred to as multi-layered networks , and have been used to characterize various complex systems, including critical infrastructure networks, cyber-physical systems, collaboration platforms, biological systems and many more. Different from single-layered networks where the functionality of their nodes is mainly affected by within-layer connections, multi-layered networks are more vulnerable to disturbance as the impact can be amplified through cross-layer dependencies, leading to the cascade failure to the entire system...
October 2017: IEEE Transactions on Knowledge and Data Engineering
Dong Zhou, Ahmed Elmokashfi
This paper investigates the possibility of saving a network that is predicted to have a cascading failure that will eventually lead to a total collapse. We model cascading failures using the recently proposed KQ model. Then predict an impending total collapse by monitoring critical slowing down indicators and subsequently attempt to prevent the total collapse of the network by adding new nodes. To this end, we systematically evaluate five node addition rules, the effect of intervention delay and network degree heterogeneity...
May 10, 2018: Scientific Reports
Rebekka Burkholz, Hans J Herrmann, Frank Schweitzer
How big is the risk that a few initial failures of nodes in a network amplify to large cascades that span a substantial share of all nodes? Predicting the final cascade size is critical to ensure the functioning of a system as a whole. Yet, this task is hampered by uncertain and missing information. In infinitely large networks, the average cascade size can often be estimated by approaches building on local tree and mean field approximations. Yet, as we demonstrate, in finite networks, this average does not need to be a likely outcome...
May 2, 2018: Scientific Reports
Yulin Zhang, Maoxian Zhao, Jionglong Su, Xiao Lu, Kebo Lv
A novel model for cascading failures in a directed logic network based on the degree strength at a node was proposed. The definitions of in-degree and out-degree strength of a node were initially reconsidered, and the load at a nonisolated node was proposed as the ratio of in-degree strength to out-degree strength of the node. The cascading failure model based on degree strength was applied to the logic network for three types of cancer including adenocarcinoma of lung, prostate cancer, and colon cancer based on their gene expression profiles...
2018: Computational and Mathematical Methods in Medicine
Mert Korkali, Jason G Veneman, Brian F Tivnan, James P Bagrow, Paul D H Hines
This corrects the article DOI: 10.1038/srep44499.
March 19, 2018: Scientific Reports
Yingrui Zhang, Alex Arenas, Osman Yağan
Robustness and cascading failures in interdependent systems has been an active research field in the past decade. However, most existing works use percolation-based models where only the largest component of each network remains functional throughout the cascade. Although suitable for communication networks, this assumption fails to capture the dependencies in systems carrying a flow (e.g., power systems, road transportation networks), where cascading failures are often triggered by redistribution of flows leading to overloading of lines...
February 2018: Physical Review. E
Raquel B De Boni, Meridith B Peratikos, Bryan E Shepherd, Beatriz Grinsztejn, Claudia Cortés, Denis Padgett, Eduardo Gotuzzo, Pablo F Belaunzarán-Zamudio, Peter F Rebeiro, Stephany N Duda, Catherine C McGowan
BACKGROUND: The HIV care cascade has improved in Latin America over the last decade. However, the influence of alcohol and noninjected drug use (NIDU) on cascade outcomes is mostly unknown. This study estimated the association of alcohol and NIDU with retention in care, loss to follow up (LTFU), and virologic failure (VF). METHODS: Individuals ≥18 years attending routine HIV clinic visits and completing the Rapid Screening Tool (RST; evaluating NIDU and ART adherence in 7-day recall period) during 2012-13 were followed up to 2015 in the Caribbean, Central and South America network for HIV epidemiology...
2018: PloS One
Zenghu Zhang, Yongfeng Yin, Xin Zhang, Lijun Liu
Controllability of complex networks has been a hot topic in recent years. Real networks regarded as interdependent networks are always coupled together by multiple networks. The cascading process of interdependent networks including interdependent failure and overload failure will destroy the robustness of controllability for the whole network. Therefore, the optimization of the robustness of interdependent network controllability is of great importance in the research area of complex networks. In this paper, based on the model of interdependent networks constructed first, we determine the cascading process under different proportions of node attacks...
2018: PloS One
Run-Ran Liu, Daniel A Eisenberg, Thomas P Seager, Ying-Cheng Lai
Previous studies of multilayer network robustness model cascading failures via a node-to-node percolation process that assumes "strong" interdependence across layers-once a node in any layer fails, its neighbors in other layers fail immediately and completely with all links removed. This assumption is not true of real interdependent infrastructures that have emergency procedures to buffer against cascades. In this work, we consider a node-to-link failure propagation mechanism and establish "weak" interdependence across layers via a tolerance parameter α which quantifies the likelihood that a node survives when one of its interdependent neighbors fails...
February 1, 2018: Scientific Reports
Huapeng Lin, Qian Zhang, Xiaocheng Li, Yushen Wu, Ye Liu, Yingchun Hu
Hepatitis B virus-associated acute liver failure (HBV-ALF) is a rare but life-threatening syndrome that carried a high morbidity and mortality. Our study aimed to explore the possible molecular mechanisms of HBV-ALF by means of bioinformatics analysis. In this study, genes expression microarray datasets of HBV-ALF from Gene Expression Omnibus were collected, and then we identified differentially expressed genes (DEGs) by the limma package in R. After functional enrichment analysis, we constructed the protein-protein interaction (PPI) network by the Search Tool for the Retrieval of Interacting Genes online database and weighted genes coexpression network by the WGCNA package in R...
February 2018: Medicine (Baltimore)
Ho Fai Po, Chi Ho Yeung, An Zeng, K Y Michael Wong
The stability of powergrid is crucial since its disruption affects systems ranging from street lightings to hospital life-support systems. While short-term dynamics of single-event cascading failures have been extensively studied, less is understood on the long-term evolution and self-organization of powergrids. In this paper, we introduce a simple model of evolving powergrid and establish its connection with the sandpile model and earthquakes, i.e., self-organized systems with intermittent strain releases...
November 2017: Physical Review. E
Xianyuan Zhan, Satish V Ukkusuri, P Suresh C Rao
We propose a new framework for modeling the evolution of functional failures and recoveries in complex networks, with traffic congestion on road networks as the case study. Differently from conventional approaches, we transform the evolution of functional states into an equivalent dynamic structural process: dual-vertex splitting and coalescing embedded within the original network structure. The proposed model successfully explains traffic congestion and recovery patterns at the city scale based on high-resolution data from two megacities...
November 2017: Physical Review. E
Nagendra K Panduranga, Jianxi Gao, Xin Yuan, H Eugene Stanley, Shlomo Havlin
Cascading failures in complex systems have been studied extensively using two different models: k-core percolation and interdependent networks. We combine the two models into a general model, solve it analytically, and validate our theoretical results through extensive simulations. We also study the complete phase diagram of the percolation transition as we tune the average local k-core threshold and the coupling between networks. We find that the phase diagram of the combined processes is very rich and includes novel features that do not appear in the models studying each of the processes separately...
September 2017: Physical Review. E
V A T Nguyen, D C Vural
Epidemics, neural cascades, power failures, and many other phenomena can be described by a diffusion process on a network. To identify the causal origins of a spread, it is often necessary to identify the triggering initial node. Here, we define a new morphological operator and use it to detect the origin of a diffusive front, given the final state of a complex network. Our method performs better than algorithms based on distance (closeness) and Jordan centrality. More importantly, our method is applicable regardless of the specifics of the forward model, and therefore can be applied to a wide range of systems such as identifying the patient zero in an epidemic, pinpointing the neuron that triggers a cascade, identifying the original malfunction that causes a catastrophic infrastructure failure, and inferring the ancestral species from which a heterogeneous population evolves...
September 2017: Physical Review. E
Jason M Samuels, Hunter B Moore, Ernest E Moore
BACKGROUND: Disseminated intravascular coagulation (DIC) remains a challenging complication of infection with inadequate treatment and significant morbidity and mortality rates. METHODS: Review of the English-language literature. RESULTS: Disseminated intravascular coagulation arises from the immune system's response to microbial invasion, as well as the byproducts of cell death that result from severe sepsis. This response triggers the coagulation system through an interconnected network of cellular and molecular signals, which developed originally as an evolutionary mechanism intended to isolate micro-organisms via fibrin mesh formation...
February 2018: Surgical Infections
Yang Yang, Adilson E Motter
In network systems, a local perturbation can amplify as it propagates, potentially leading to a large-scale cascading failure. Here we derive a continuous model to advance our understanding of cascading failures in power-grid networks. The model accounts for both the failure of transmission lines and the desynchronization of power generators and incorporates the transient dynamics between successive steps of the cascade. In this framework, we show that a cascade event is a phase-space transition from an equilibrium state with high energy to an equilibrium state with lower energy, which can be suitably described in a closed form using a global Hamiltonian-like function...
December 15, 2017: Physical Review Letters
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