共查询到20条相似文献,搜索用时 15 毫秒
1.
In this paper, we propose an evolving Sierpinski gasket, based on which we establish a model of evolutionary Sierpinski networks (ESNs) that unifies deterministic Sierpinski network [Z.Z. Zhang, S.G. Zhou, T. Zou, L.C. Chen, J.H. Guan, Eur. Phys. J. B 60 (2007) 259] and random Sierpinski network [Z.Z. Zhang, S.G. Zhou, Z. Su, T. Zou, J.H. Guan, Eur. Phys. J. B 65 (2008) 141] to the same framework. We suggest an iterative algorithm generating the ESNs. On the basis of the algorithm, some relevant properties of presented networks are calculated or predicted analytically. Analytical solution shows that the networks under consideration follow a power-law degree distribution, with the distribution exponent continuously tuned in a wide range. The obtained accurate expression of clustering coefficient, together with the prediction of average path length reveals that the ESNs possess small-world effect. All our theoretical results are successfully contrasted by numerical simulations. Moreover, the evolutionary prisoner’s dilemma game is also studied on some limitations of the ESNs, i.e., deterministic Sierpinski network and random Sierpinski network. 相似文献
2.
Zhongzhi Zhang Shuigeng Zhou Tao Zou Lichao Chen Jihong Guan 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,60(2):259-264
We make a mapping from Sierpinski fractals to a new class
of networks, the incompatibility networks, which are scale-free,
small-world, disassortative, and maximal planar graphs. Some
relevant characteristics of the networks such as degree
distribution, clustering coefficient, average path length, and
degree correlations are computed analytically and found to be
peculiarly rich. The method of network representation can be applied
to some real-life systems making it possible to study the complexity
of real networked systems within the framework of complex network
theory. 相似文献
3.
G. Ghoshal M. E.J. Newman 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,58(2):175-184
We consider distributed networks, such as peer-to-peer networks, whose
structure can be manipulated by adjusting the rules by which vertices
enter and leave the network. We focus in particular on degree
distributions and show that, with some mild constraints, it is possible
by a suitable choice of rules to arrange for the network to have any
degree distribution we desire. We also describe a mechanism based on
biased random walks by which appropriate rules could be implemented in
practice. As an example application, we describe and simulate the
construction of a peer-to-peer network optimized to minimize search times
and bandwidth requirements. 相似文献
4.
A. P. Quayle A. S. Siddiqui S. J.M. Jones 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,50(4):617-630
We propose a model of an underlying mechanism responsible for the formation of assortative mixing in networks between “similar”
nodes or vertices based on generic vertex properties. Existing models focus on a particular type of assortative mixing, such
as mixing by vertex degree, or present methods of generating a network with certain properties, rather than modeling a mechanism
driving assortative mixing during network growth. The motivation is to model assortative mixing by non-topological vertex
properties, and the influence of these non-topological properties on network topology. The model is studied in detail for
discrete and hierarchical vertex properties, and we use simulations to study the topology of resulting networks. We show that
assortative mixing by generic properties directly drives the formation of community structure beyond a threshold assortativity
of r ∼0.5, which in turn influences other topological properties. This direct relationship is demonstrated by introducing
a new measure to characterise the correlation between assortative mixing and community structure in a network. Additionally,
we introduce a novel type of assortative mixing in systems with hierarchical vertex properties, from which a hierarchical
community structure is found to result.
Electronic supplementary material Supplementary Online Material 相似文献
5.
Zhongzhi Zhang Shuigeng Zhou Lichao Chen 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,58(3):337-344
We present a family of scale-free network model consisting
of cliques, which is established by a simple recursive algorithm. We
investigate the networks both analytically and numerically. The
obtained analytical solutions show that the networks follow a
power-law degree distribution, with degree exponent continuously
tuned between 2 and 3. The exact expression of clustering
coefficient is also provided for the networks. Furthermore, the
investigation of the average path length reveals that the networks
possess small-world feature. Interestingly, we find that a special
case of our model can be mapped into the Yule process. 相似文献
6.
We investigated the topological properties of stock networks constructed by a minimal spanning tree. We compared the original stock network with the estimated network; the original network is obtained by the actual stock returns, while the estimated network is the correlation matrix created by random matrix theory. We found that the consistency between the two networks increases as more eigenvalues are considered. In addition, we suggested that the largest eigenvalue has a significant influence on the formation of stock networks. 相似文献
7.
The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices. 相似文献
8.
Unified index to quantifying heterogeneity of complex networks 总被引:1,自引:0,他引:1
Hai-Bo Hu 《Physica A》2008,387(14):3769-3780
Although recent studies have revealed that degree heterogeneity of a complex network has significant impact on the network performance and function, a unified definition of the heterogeneity of a network with any degree distribution is absent. In this paper, we define a heterogeneity index 0≤H<1 to quantify the degree heterogeneity of any given network. We analytically show the existence of an upper bound of H=0.5 for exponential networks, thus explain why exponential networks are homogeneous. On the other hand, we also analytically show that the heterogeneity index of an infinite power law network is between 1 and 0.5 if and only if its degree exponent is between 2 and 2.5. We further show that for any power law network with a degree exponent greater than 2.5, there always exists an exponential network such that both networks have the same heterogeneity index. This may help to explain why 2.5 is a critical degree exponent for some dynamic behaviors on power law networks. 相似文献
9.
B. Karrer G. Ghoshal 《The European Physical Journal B - Condensed Matter and Complex Systems》2008,62(2):239-245
There has been a considerable amount of interest in recent years on the robustness of networks to failures. Many previous
studies have concentrated on the effects of node and edge removals on the connectivity structure of a static network; the networks are considered to be static in the sense that no compensatory measures are allowed for recovery of
the original structure. Real world networks such as the world wide web, however, are not static and experience a considerable
amount of turnover, where nodes and edges are both added and deleted. Considering degree-based node removals, we examine the
possibility of preserving networks from these types of disruptions. We recover the original degree distribution by allowing
the network to react to the attack by introducing new nodes and attaching their edges via specially tailored schemes. We focus
particularly on the case of non-uniform failures, a subject that has received little attention in the context of evolving
networks. Using a combination of analytical techniques and numerical simulations, we demonstrate how to preserve the exact degree distribution of the studied networks from various forms of attack. 相似文献
10.
Zhongzhi Zhang Shuigeng Zhou Yi Qi Jihong Guan 《The European Physical Journal B - Condensed Matter and Complex Systems》2008,63(4):507-513
The uniform recursive tree (URT) is one of the most important models and has been successfully applied to many fields. Here
we study exactly the topological characteristics and spectral properties of the Laplacian matrix of a deterministic uniform
recursive tree, which is a deterministic version of URT. Firstly, from the perspective of complex networks, we determine the
main structural characteristics of the deterministic tree. The obtained vigorous results show that the network has an exponential
degree distribution, small average path length, power-law distribution of node betweenness, and positive degree-degree correlations.
Then we determine the complete Laplacian spectra (eigenvalues) and their corresponding eigenvectors of the considered graph.
Interestingly, all the Laplacian eigenvalues are distinct. 相似文献
11.
The backbone of a city 总被引:1,自引:0,他引:1
S. Scellato A. Cardillo V. Latora S. Porta 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,50(1-2):221-225
Recent studies have revealed the importance of centrality measures
to analyze various spatial factors affecting human life in cities.
Here we show how it is possible to extract the backbone of a city
by deriving spanning trees based on edge betweenness and edge
information.
By using as sample cases the cities of Bologna and San Francisco,
we show how the obtained trees are radically different from those
based on edge lengths, and allow an extended comprehension of
the “skeleton” of most important routes that so much affects
pedestrian/vehicular flows, retail commerce vitality, land-use
separation, urban crime and collective dynamical behaviours. 相似文献
12.
K. M. Mogare D. V. Sheptyakov R. Bircher H.-U. Güdel M. Jansen 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,52(3):371-376
We present a novel model to simulate real social networks of complex
interactions, based in a system of colliding particles
(agents).
The network is build by keeping track of the collisions and evolves in
time with correlations which emerge due to the mobility of the agents.
Therefore, statistical features are a consequence only of local
collisions among its individual agents.
Agent dynamics is realized by an event-driven algorithm of collisions
where energy is gained as opposed to physical systems which have
dissipation.
The model reproduces empirical data from networks of sexual
interactions, not previously obtained with other approaches. 相似文献
13.
E. Estrada 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,52(4):563-574
We study the property of certain complex networks of being both sparse and
highly connected, which is known as “good expansion” (GE). A network has
GE properties if every subset S of nodes (up to 50% of the nodes) has a
neighborhood that is larger than some “expansion factor” φ
multiplied by the number of nodes in S. Using a graph spectral method we
introduce here a new parameter measuring the good expansion character of a
network. By means of this parameter we are able to classify 51 real-world
complex networks — technological, biological, informational, biological and
social — as GENs or non-GENs. Combining GE properties and node degree
distribution (DD) we classify these complex networks in four different
groups, which have different resilience to intentional attacks against their
nodes. The simultaneous existence of GE properties and uniform degree
distribution contribute significantly to the robustness in complex networks.
These features appear solely in 14% of the 51 real-world networks studied
here. At the other extreme we find that ∼40% of all networks are
very vulnerable to targeted attacks. They lack GE properties, display skewed
DD — exponential or power-law — and their topologies are changed more
dramatically by targeted attacks directed at bottlenecks than by the removal
of network hubs. 相似文献
14.
We theoretically and numerically investigated the threshold network model with a generic weight function where there were a large number of nodes and a high threshold. Our analysis was based on extreme value theory, which gave us a theoretical understanding of the distribution of independent and identically distributed random variables within a sufficiently high range. Specifically, the distribution could be generally expressed by a generalized Pareto distribution, which enabled us to formulate the generic weight distribution function. By using the theorem, we obtained the exact expressions of degree distribution and clustering coefficient which behaved as universal power laws within certain ranges of degrees. We also compared the theoretical predictions with numerical results and found that they were extremely consistent. 相似文献
15.
Inspiring Newton's law of universal gravitation and empirical studies, we propose a concept of virtual network mass and network gravitational force in complex networks. Then a network gravitational model for complex networks is presented. In the model, each node in the network is described with its position, edges (links) and virtual network mass. The proposed model is examined by experiments to show its potential applications. 相似文献
16.
J. M. Kumpula J. Saramäki K. Kaski J. Kertész 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,56(1):41-45
According to Fortunato and Barthélemy, modularity-based community detection
algorithms have a resolution threshold such that small communities in a large
network are invisible. Here we generalize their work and show that the q-state
Potts community detection method introduced by Reichardt and Bornholdt
also has a resolution threshold. The model contains a parameter by which this threshold can be tuned, but no a priori principle
is known to select the proper value.
Single global optimization criteria do not seem capable for detecting all
communities if their size distribution is broad. 相似文献
17.
L. Tian D.-N. Shi 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,56(2):167-171
In this paper, we study a rank-based model for weighted network. The evolution rule of the network is based on the ranking
of node strength, which couples the topological growth and the weight dynamics. Analytically and by simulations, we demonstrate
that the generated networks recover the scale-free distributions of degree and strength in the whole region of the growth
dynamics parameter (α>0). Moreover, this network evolution mechanism can also produce scale-free property of weight, which
adds deeper comprehension of the networks growth in the presence of incomplete information. We also characterize the clustering
and correlation properties of this class of networks. It is showed that at α=1 a structural phase transition occurs, and for
α>1 the generated network simultaneously exhibits hierarchical organization and disassortative degree correlation, which is
consistent with a wide range of biological networks. 相似文献
18.
In this paper, adopting the initial load of a node i to be with ki being the degree of the node i, we propose a cascading model based on a load local redistribution rule and examine cascading failures on the typical network, i.e., the BA network with the scale-free property. We find that the BA scale-free network reaches the strongest robustness level in the case of α=1 and the robustness of the network has a positive correlation with the average degree 〈k〉, where the robustness is quantified by a transition from normal state to collapse. In addition, we further discuss the effects of two different attacks for the robustness against cascading failures on our cascading model and find an interesting result, i.e., the effects of two different attacks, strongly depending to the value α. These results may be very helpful for real-life networks to avoid cascading-failure-induced disasters. 相似文献
19.
V. Zlatic G. Bianconi A. Díaz-Guilera D. Garlaschelli F. Rao G. Caldarelli 《The European Physical Journal B - Condensed Matter and Complex Systems》2009,67(3):271-275
For many complex networks present in nature only a single instance, usually of large size, is available. Any measurement made
on this single instance cannot be repeated on different realizations. In order to detect significant patterns in a real-world
network it is therefore crucial to compare the measured results with a null model counterpart. Here we focus on dense and
weighted networks, proposing a suitable null model and studying the behaviour of the degree correlations as measured by the
rich-club coefficient. Our method solves an existing problem with the randomization of dense unweighted graphs, and at the
same time represents a generalization of the rich-club coefficient to weighted networks which is complementary to other recently
proposed ones. 相似文献
20.
Empirical mode decomposition (EMD) method can decompose any complicated data into finite ‘intrinsic mode functions’ (IMFs). In this paper, we use EMD method to analyze and discuss the structural properties of complex networks. A random-walk method is used to collect the data series of network systems. Utilizing the EMD method, we decompose the obtained data into finite IMFs under different spatial scales. The analysis results show that EMD method is an effective tool for capturing the topological properties of network systems under different spatial scales, such as the modular structures of network systems and their energy densities. 相似文献