LOAD DISTRIBUTION IN CONGESTED SCALE-FREE NETWORKS

2009 ◽  
Vol 20 (02) ◽  
pp. 197-207 ◽  
Author(s):  
JIAN-FENG ZHENG ◽  
ZI-YOU GAO ◽  
BAI-BAI FU

In this work, we study the effects of scale-free topology and congestion on load distribution. Congestion effect can be described by link cost functions, which map link flows into travel times. Two different kinds of link's practical capacity (it is similar to link's capacity for transport) which is a parameter in link cost functions, i.e., uniform case and nonuniform case, are investigated. After introducing the effect of congestion, load distribution is typically discussed in Barábasi–Albert and Goh scale-free networks. In the uniform case, for Barábasi–Albert scale-free networks, we recover a power-law behavior for load distribution with a larger exponent, as compared with the distribution of betweenness centrality; for Goh scale-free networks, we also recover a power-law behavior and its exponent approaches to the exponent of degree distribution. While in the nonuniform case, the power-law behavior for load distribution may not always be conserved in both Barábasi–Albert and Goh scale-free networks. That is to say, different kinds of load distributions are obtained under different conditions. It may shed some light to study traffic dynamics on scale-free networks.

2010 ◽  
Vol 21 (08) ◽  
pp. 991-999 ◽  
Author(s):  
JIAN-FENG ZHENG ◽  
LING-XIAO YANG ◽  
ZI-YOU GAO ◽  
BAI-BAI FU

In this work, we study the effect of congestion on the behavior of cascading failures in scale-free networks, where a capacity is assigned on each node (controlled by a tolerance parameter α), and traffic flows are governed by user equilibrium instead of going along the shortest paths. The effect of congestion can be described by link cost function, which denotes the time needed to travel along the link. Here we focus on studying the effect of link's practical capacity, which is a parameter in link cost function. Two different kinds of link's practical capacity are investigated, i.e. uniform case and nonuniform case. In the uniform case, each link has the same value of practical capacity. While in the nonuniform case, we assume that link's practical capacity and degrees of the link's endpoints are correlated (controlled by parameter θ, which governs the heterogeneity of link's practical capacity). Simulation results show that, in the uniform case, scale-free networks are more prone to cascading failures when increasing the value of link's practical capacity. In the nonuniform case, cascading failures in scale-free networks are very sensitive to α when θ > 0; while θ < 0, scale-free networks may suffer from serious cascading failures, regardless of α.


2014 ◽  
Vol 25 (10) ◽  
pp. 1450055 ◽  
Author(s):  
Hao-Ming Du ◽  
Zi-You Gao ◽  
Zhi-Hong Zhu ◽  
Jian-Feng Zheng

Traffic demand is one of the most important factors to affect the traffic flow pattern or load distribution in congested networks. In this paper, we investigate the load distributions and relations between the load and degree of the node for different traffic demands in scale-free networks. Different kinds of load distributions are obtained under different traffic demands. Furthermore, the impact of link capacity on load distribution in congested scale-free networks is also discussed.


2007 ◽  
Vol 56 (10) ◽  
pp. 5635
Author(s):  
Guo Jin-Li ◽  
Wang Li-Na

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Shuping Li ◽  
Zhen Jin

We present a heterogeneous networks model with the awareness stage and the decision-making stage to explain the process of new products diffusion. If mass media is neglected in the decision-making stage, there is a threshold whether the innovation diffusion is successful or not, or else it is proved that the network model has at least one positive equilibrium. For networks with the power-law degree distribution, numerical simulations confirm analytical results, and also at the same time, by numerical analysis of the influence of the network structure and persuasive advertisements on the density of adopters, we give two different products propagation strategies for two classes of nodes in scale-free networks.


2017 ◽  
Vol 28 (05) ◽  
pp. 1750064 ◽  
Author(s):  
A. Ould Baba ◽  
O. Bamaarouf ◽  
A. Rachadi ◽  
H. Ez-Zahraouy

Using numerical simulations, we investigate the effects of the connectivity and topologies of network on the quality of transport between connected scale free networks. Hence, the flow as the electrical conductance between connected networks is calculated. It is found that the conductance distribution between networks follow a power law [Formula: see text] where [Formula: see text] is the exponent of the global Network of network, we show that the transport in the symmetric growing preferential attachment connection is more efficient than the symmetric static preferential attachment connection. Furthermore, the differences of transport and networks communications properties in the different cases are discussed.


2013 ◽  
Vol 753-755 ◽  
pp. 2959-2962
Author(s):  
Jun Tao Yang ◽  
Hui Wen Deng

Assigning the value of interest to each node in the network, we give a scale-free network model. The value of interest is related to the fitness and the degree of the node. Experimental results show that the interest model not only has the characteristics of the BA scale-free model but also has the characteristics of fitness model, and the network has a power-law distribution property.


2018 ◽  
Vol 21 ◽  
pp. 00012
Author(s):  
Andrzej Paszkiewicz

The paper concerns the use of the scale-free networks theory and the power law in designing wireless networks. An approach based on generating random networks as well as on the classic Barabási-Albert algorithm were presented. The paper presents a new approach taking the limited resources for wireless networks into account, such as available bandwidth. In addition, thanks to the introduction of opportunities for dynamic node removal it was possible to realign processes occurring in wireless networks. After introduction of these modifications, the obtained results were analyzed in terms of a power law and the degree distribution of each node.


2007 ◽  
Vol 17 (07) ◽  
pp. 2447-2452 ◽  
Author(s):  
S. BOCCALETTI ◽  
D.-U. HWANG ◽  
V. LATORA

We introduce a fully nonhierarchical network growing mechanism, that furthermore does not impose explicit preferential attachment rules. The growing procedure produces a graph featuring power-law degree and clustering distributions, and manifesting slightly disassortative degree-degree correlations. The rigorous rate equations for the evolution of the degree distribution and for the conditional degree-degree probability are derived.


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