Cascading failures in complex networks with community structure

2014 ◽  
Vol 25 (05) ◽  
pp. 1440005 ◽  
Author(s):  
Guoqiang Lin ◽  
Zengru Di ◽  
Ying Fan
Keyword(s):  
Community Structure ◽  
Community Networks ◽  
Random Networks ◽  
Cascading Failures ◽  
Power Law Distribution ◽  
Avalanche Size ◽  
Scale Free ◽  
High Betweenness ◽  
Failure Scenario ◽  
The Relationship

Much empirical evidence shows that when attacked with cascading failures, scale-free or even random networks tend to collapse more extensively when the initially deleted node has higher betweenness. Meanwhile, in networks with strong community structure, high-betweenness nodes tend to be bridge nodes that link different communities, and the removal of such nodes will reduce only the connections among communities, leaving the networks fairly stable. Understanding what will affect cascading failures and how to protect or attack networks with strong community structure is therefore of interest. In this paper, we have constructed scale-free Community Networks (SFCN) and Random Community Networks (RCN). We applied these networks, along with the Lancichinett–Fortunato–Radicchi (LFR) benchmark, to the cascading-failure scenario to explore their vulnerability to attack and the relationship between cascading failures and the degree distribution and community structure of a network. The numerical results show that when the networks are of a power-law distribution, a stronger community structure will result in the failure of fewer nodes. In addition, the initial removal of the node with the highest betweenness will not lead to the worst cascading, i.e. the largest avalanche size. The Betweenness Overflow (BOF), an index that we developed, is an effective indicator of this tendency. The RCN, however, display a different result. In addition, the avalanche size of each node can be adopted as an index to evaluate the importance of the node.

SZNAJD MODEL AND PROPORTIONAL ELECTIONS: THE ROLE OF THE TOPOLOGY OF THE NETWORK

2009 ◽  
Vol 20 (06) ◽  
pp. 979-990 ◽  
Author(s):  
FABIO STUCCHI VANNUCCHI ◽  
CARMEN P. C. PRADO
Keyword(s):  
Community Structure ◽  
Order Parameter ◽  
High Dimensionality ◽  
Power Law Distribution ◽  
Scale Free ◽  
Absorbing State ◽  
Regular Lattices ◽  
Scale Properties ◽  
Proportional Elections

The Sznajd model (SM) has been employed with success in the last years to describe opinion propagation in a community. In particular, it has been claimed that its transient is able to reproduce some scale properties observed in data of proportional elections, in different countries, if the community structure (the network) is scale-free. In this work, we investigate the properties of the transient of a particular version of the SM, introduced by Bernardes and co-authors in 2002. We studied the behavior of the model in networks of different topologies through the time evolution of an order parameter known as interface density, and concluded that regular lattices with high dimensionality also leads to a power-law distribution of the number of candidates with v votes. Also, we show that the particular absorbing state achieved in the stationary state (or else, the winner candidate), is related to a particular feature of the model, that may not be realistic in all situations.

Cascading failures in interdependent modular networks with partial random coupling preference

2017 ◽  
Vol 31 (29) ◽  
pp. 1750267 ◽  
Author(s):  
Meng Tian ◽  
Xianpei Wang ◽  
Zhengcheng Dong ◽  
Guowei Zhu ◽  
Jiachuang Long ◽  
...  
Keyword(s):  
Community Structure ◽  
Network Robustness ◽  
Cascading Failures ◽  
Scale Free ◽  
Interdependent Networks ◽  
Connection Probability ◽  
Random Coupling ◽  
Protection Cost ◽  
Interdependent Infrastructures ◽  
Partial Coupling

Cascading failures have been widely analyzed in interdependent networks with different coupling preferences from microscopic and macroscopic perspectives in recent years. Plenty of real-world interdependent infrastructures, representing as interdependent networks, exhibit community structure, one of the most important mesoscopic structures, and partial coupling preferences, which can affect cascading failures in interdependent networks. In this paper, we propose the partial random coupling in communities, investigating cascading failures in interdependent modular scale-free networks under inner attacks and hub attacks. We mainly analyze the effects of the discoupling probability and the intermodular connection probability on cascading failures in interdependent networks. We find that increasing either the dicoupling probability or the intermodular connection probability can enhance the network robustness under both hub attacks and inner attacks. We also note that the community structure can prevent cascading failures spreading globally in entire interdependent networks. Finally, we obtain the result that if we want to efficiently improve the robustness of interdependent networks and reduce the protection cost, the intermodular connection probability should be protected preferentially, implying that improving the robustness of a single network is the fundamental method to enhance the robustness of the entire interdependent networks.

scholarly journals Emergence of Scaling in Random Networks

Science ◽  
1999 ◽  
Vol 286 (5439) ◽  
pp. 509-512 ◽  
Author(s):  
Albert-László Barabási ◽  
Réka Albert
Keyword(s):  
Common Property ◽  
World Wide ◽  
Genetic Networks ◽  
Random Networks ◽  
Power Law Distribution ◽  
Large Networks ◽  
Scale Free ◽  
The World ◽  
Complex Topology ◽  
The Individual

Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

scholarly journals SPECTRAL METHODS CLUSTER WORDS OF THE SAME CLASS IN A SYNTACTIC DEPENDENCY NETWORK

2007 ◽  
Vol 17 (07) ◽  
pp. 2453-2463 ◽  
Author(s):  
RAMON FERRER I CANCHO ◽  
ANDREA CAPOCCI ◽  
GUIDO CALDARELLI
Keyword(s):  
Community Structure ◽  
Spectral Methods ◽  
Null Hypothesis ◽  
Cluster Size ◽  
Small World ◽  
Power Law Distribution ◽  
Long Range Correlations ◽  
Scale Free ◽  
Dependency Network ◽  
Syntactic Dependency

We analyze here a particular kind of linguistic network where vertices represent words and edges stand for syntactic relationships between words. The statistical properties of these networks have been recently studied and various features such as the small-world phenomenon and a scale-free distribution of degrees have been found. Our work focuses on four classes of words: verbs, nouns, adverbs and adjectives. Here, we use spectral methods sorting vertices. We show that the ordering clusters words of the same class. For nouns and verbs, the cluster size distribution clearly follows a power-law distribution that cannot be explained by a null hypothesis. Long-range correlations are found between vertices in the ordering provided by the spectral method. The findings support the use of spectral methods for detecting community structure.

scholarly journals Identifying Vulnerable Nodes of Complex Networks in Cascading Failures Induced by Node-Based Attacks

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Shudong Li ◽  
Lixiang Li ◽  
Yan Jia ◽  
Xinran Liu ◽  
Yixian Yang
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Small World ◽  
Cascading Failures ◽  
Small World Networks ◽  
Power Law Distribution ◽  
Scale Free ◽  
Potential Safety ◽  
High Degree ◽  
Fourth Kind

In the research on network security, distinguishing the vulnerable components of networks is very important for protecting infrastructures systems. Here, we probe how to identify the vulnerable nodes of complex networks in cascading failures, which was ignored before. Concerned with random attack (RA) and highest load attack (HL) on nodes, we model cascading dynamics of complex networks. Then, we introduce four kinds of weighting methods to characterize the nodes of networks including Barabási-Albert scale-free networks (SF), Watts-Strogatz small-world networks (WS), Erdos-Renyi random networks (ER), and two real-world networks. The simulations show that, for SF networks under HL attack, the nodes with small value of the fourth kind of weight are the most vulnerable and the ones with small value of the third weight are also vulnerable. Also, the real-world autonomous system with power-law distribution verifies these findings. Moreover, for WS and ER networks under both RA and HL attack, when the nodes have low tolerant ability, the ones with small value of the fourth kind of weight are more vulnerable and also the ones with high degree are easier to break down. The results give us important theoretical basis for digging the potential safety loophole and making protection strategy.

PLAYING WITH FIRE COLLECTIVELY: CONTEMPORARY CULTURAL RITES AS DEVISERS AND OUTCOMES OF COMMUNITY NETWORKS

2020 ◽  
Author(s):  
Alba Colombo ◽  
Jaime Altuna ◽  
Esther Oliver-Grasiot
Keyword(s):  
Social Networks ◽  
Social Context ◽  
Power Relations ◽  
Symbolic Capital ◽  
Community Networks ◽  
Mutual Dependence ◽  
Community Solidarity ◽  
Symbolic Content ◽  
The Relationship

Popular festivities and traditional events are important moments in which symbolic content, deep emotions and community solidarity are developed. However, there has been little research on the relationship between such events and their social networks and the power relations within these networks. This paper explores the ability of community events and networks to reflect and strengthen social context. Rather than observing the capacity of the event to generate a network, we focus on identifying how the event network is constructed, and how it creates relationships between the different groups, or nodes, within broader social networks. The case analysed is the Correfoc de la Mercè, a traditional firework event in Barcelona involving the Colles de diables, or Catalan popular fire culture groups. Our findings show that there is a bidirectional link or a mutual dependence between the groups (or nodes) and the event, which also support the development of shared social and symbolic capital.

scholarly journals Analysis on Invulnerability of Wireless Sensor Network towards Cascading Failures Based on Coupled Map Lattice

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xiuwen Fu ◽  
Yongsheng Yang ◽  
Haiqing Yao
Keyword(s):  
Random Network ◽  
Small World ◽  
Coupled Map Lattice ◽  
Wireless Sensor ◽  
Cascading Failures ◽  
Scale Free Network ◽  
Scale Free ◽  
Network Topologies ◽  
Free Network ◽  
Entire Network

Previous research of wireless sensor networks (WSNs) invulnerability mainly focuses on the static topology, while ignoring the cascading process of the network caused by the dynamic changes of load. Therefore, given the realistic features of WSNs, in this paper we research the invulnerability of WSNs with respect to cascading failures based on the coupled map lattice (CML). The invulnerability and the cascading process of four types of network topologies (i.e., random network, small-world network, homogenous scale-free network, and heterogeneous scale-free network) under various attack schemes (i.e., random attack, max-degree attack, and max-status attack) are investigated, respectively. The simulation results demonstrate that the rise of interference R and coupling coefficient ε will increase the risks of cascading failures. Cascading threshold values Rc and εc exist, where cascading failures will spread to the entire network when R>Rc or ε>εc. When facing a random attack or max-status attack, the network with higher heterogeneity tends to have a stronger invulnerability towards cascading failures. Conversely, when facing a max-degree attack, the network with higher uniformity tends to have a better performance. Besides that, we have also proved that the spreading speed of cascading failures is inversely proportional to the average path length of the network and the increase of average degree k can improve the network invulnerability.

A Discovery Method of the Dirty Data Transmission Path Based on Complex Network

2014 ◽  
Vol 651-653 ◽  
pp. 1741-1747
Author(s):  
Xiao Lin Zhao ◽  
Gang Hao ◽  
Chang Zhen Hu ◽  
Zhi Qiang Li
Keyword(s):  
Complex Network ◽  
Data Transmission ◽  
Software System ◽  
Power Law Distribution ◽  
Scale Free ◽  
Transmission Path ◽  
Binary File ◽  
Weighted Directed Graph ◽  
Dirty Data ◽  
Discovery Method

With the increasing scale of software system, the interaction between software elements becomes more and more complex, which lead to the increased dirty data in running software system. This may reduce the system performance and cause system collapse. In this paper, we proposed a discovery method of the dirty data transmission path based on complex network. Firstly, the binary file is decompiled and the function call graph is drawn by using the source code. Then the software structure is described as a weighted directed graph based on the knowledge of complex network. In addition, the dirty data node is marked by using the power-law distribution characteristics of the scale-free network construction of complex network chart. Finally, we found the dirty data transmission path during software running process. The experimental results show the transmission path of dirty data is accurate, which confirmed the feasibility of the method.

CAPACITY ASSIGNMENT MODEL TO DEFENSE CASCADING FAILURES

2009 ◽  
Vol 20 (07) ◽  
pp. 991-999 ◽  
Author(s):  
J. J. WU ◽  
H. J. SUN ◽  
Z. Y. GAO
Keyword(s):  
Traffic Flow ◽  
Cascading Failures ◽  
Traffic Networks ◽  
Practical Application ◽  
Assignment Rule ◽  
Scale Free ◽  
Capacity Assignment ◽  
Assignment Model ◽  
Equilibrium Assignment ◽  
Theoretical Significance

How to alleviate the damages of cascading failures triggered by the overload of edges/nodes is common in complex networks. To describe the whole cascading failures process from edges overloading to nodes malfunctioning and the dynamic spanning clustering with the evolvement of traffic flow, we propose a capacity assignment model by introducing an equilibrium assignment rule of flow in artificially created scale-free traffic networks. Additionally, the capacity update rule of node is given in this paper. We show that a single failed edge may undergo the cascading failures of nodes, and a small failure has the potential to trigger a global cascade. It is suggested that enhancing the capacity of node is particularly important for the design of any complex network to defense the cascading failures. Meanwhile, it has very important theoretical significance and practical application worthiness in the development of effective methods to alleviate the damage of one or some failed edges/nodes.

scholarly journals Rare microbes from diverse Earth biomes dominate community activity

2019 ◽  
Author(s):  
Rohan Sachdeva ◽  
Barbara J. Campbell ◽  
John F. Heidelberg
Keyword(s):  
Community Structure ◽  
Microbial Activity ◽  
Ecosystem Function ◽  
Total Activity ◽  
Reaction Rates ◽  
Community Activity ◽  
Crucial Component ◽  
Tightly Coupled ◽  
The Relationship

AbstractMicrobes are the Earth’s most numerous organisms and are instrumental in driving major global biological and chemical processes. Microbial activity is a crucial component of all ecosystems, as microbes have the potential to control any major biochemical process. In recent years, considerable strides have been made in describing the community structure,i.e. diversity and abundance, of microbes from the Earth’s major biomes. In virtually all environments studied, a few highly abundant taxa dominate the structure of microbial communities. Still, microbial diversity is high and is concentrated in the less abundant, or rare, fractions of the community,i.e. the “long tail” of the abundance distribution. The relationship between microbial community structure and activity, specifically the role of rare microbes, and its connection to ecosystem function, is not fully understood. We analyzed 12.3 million metagenomic and metatranscriptomic sequence assemblies and their genes from environmental, human, and engineered microbiomes, and show that microbial activity is dominated by rare microbes (96% of total activity) across all measured biomes. Further, rare microbial activity was comprised of traits that are fundamental to ecosystem and organismal health,e.g. biogeochemical cycling and infectious disease. The activity of rare microbes was also tightly coupled to temperature, revealing a link between basic biological processes,e.g. reaction rates, and community activity. Our study provides a broadly applicable and predictable paradigm that implicates rare microbes as the main microbial drivers of ecosystem function and organismal health.

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