The Detection Method of Network Topological Property Based on Multiple Sampling

2012 ◽  
Vol 256-259 ◽  
pp. 2396-2400
Author(s):  
Cong Huang ◽  
D G Zhang ◽  
T J Yang ◽  
H Yang
Keyword(s):  
Topological Property ◽  
Detection Method ◽  
Sampling Frequency ◽  
Average Degree ◽  
Global Networks ◽  
Scale Free ◽  
Multiple Sampling ◽  
Scale Free Networks ◽  
Sampling Probability

Recent studies have shown that subnets of scale-free networks are not scale-free, which make it difficult to extrapolate from subnet data to properties of the global networks. Here, we discuss sampling properties of Erdö–Rényi and scale-free networks, then figure out how average degree varies with sampling probability. This finding is developed to be a practical detection method based on multiple sampling. In practice, the method could not only prove global networks and randomly sampled subnets belong to the same family of probability, but also detect unknown networks by least sampling frequency.

A NEW ATTACK ON SCALE-FREE NETWORKS BASED ON CASCADING FAILURES

2009 ◽  
Vol 23 (20n21) ◽  
pp. 2497-2505 ◽  
Author(s):  
KAI YU ◽  
LILI RONG ◽  
JIANWEI WANG
Keyword(s):  
Real Life ◽  
Local Information ◽  
Average Degree ◽  
Cascading Failure ◽  
Cascading Failures ◽  
Scale Free ◽  
Scale Free Networks ◽  
Key Nodes ◽  
Attack Strategy

In this paper, based on the local information about nodes, we propose a new attack strategy, considering the average degree of the node's neighboring nodes. Adopting the cascading model proposed in Chin. Phys. Lett.25(10) (2008) 3826, we investigate the effect of the new attack strategy for the robustness against cascading failures on a typical network, i.e. BA scale-free networks. Compared with two attacks on the nodes with the highest load or the lowest load, numerically we find that our presented attack is the most efficient way to destruct the BA scale-free networks in the case of α ≤ 0.6, where α is a tunable parameter and determines to the load strength of a node. In addition, we also find that the efficiency of the new attack strategy is more obvious near the parameter α = 0.5. We expect our findings to provide insights into the protection of the key nodes for real-life networks to avoid cascading-failure-induced disasters.

Cascading Failures in Two-Layered Interdependent Scale-Free Networks

2013 ◽  
Vol 419 ◽  
pp. 918-924
Author(s):  
Xing Zhao Peng ◽  
Hong Yao ◽  
Jun Du ◽  
Chao Ding ◽  
Zhi Hao Zhang
Keyword(s):  
Average Degree ◽  
Cascading Failures ◽  
Failure Model ◽  
Cascading Effects ◽  
Scale Free ◽  
Interdependent Networks ◽  
The Past ◽  
Interdependent Network ◽  
Scale Free Networks ◽  
Random Failures

Cascading failures in isolated networks have been widely studied in the past decade, cascading failures in interdependent networks are attracting more and more attention recently, but previous studies focus on the interdependent networks topological cascading effects, neglecting the loads which present in most real networks. Considering the effect of loads, the two-layered interdependent BA network model and the cascading failure model were reestablished in this paper, based on these, the robustness of interdependent networks under random failures and intentional attacks and the effects of average degree on the suppressing of cascading failures were researched. The simulation results show that compared to random failures, interdependent network is more vulnerable under intentional attacks; the network in coupled state is more vulnerable than in isolated state under random failures, while therere no obvious differences under intentional attacks; the network performs more robust to resist cascading failures if each layer network of the interdependent network hold larger average degree.

scholarly journals Invasion of Cooperation in Scale-Free Networks: Accumulated versus Average Payoffs

2017 ◽  
Vol 23 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Genki Ichinose ◽  
Hiroki Sayama
Keyword(s):  
Evolutionary Dynamics ◽  
Evolutionarily Stable Strategy ◽  
Average Degree ◽  
Structured Populations ◽  
Evolution Of Cooperation ◽  
Scale Free ◽  
Invasion Mechanism ◽  
Cooperative Strategies ◽  
Average Payoff ◽  
Scale Free Networks

It is well known that cooperation cannot be an evolutionarily stable strategy for a non-iterative game in a well-mixed population. In contrast, structured populations favor cooperation, since cooperators can benefit each other by forming local clusters. Previous studies have shown that scale-free networks strongly promote cooperation. However, little is known about the invasion mechanism of cooperation in scale-free networks. To study microscopic and macroscopic behaviors of cooperators' invasion, we conducted computational experiments on the evolution of cooperation in scale-free networks where, starting from all defectors, cooperators can spontaneously emerge by mutation. Since the evolutionary dynamics are influenced by the definition of fitness, we tested two commonly adopted fitness functions: accumulated payoff and average payoff. Simulation results show that cooperation is strongly enhanced with the accumulated payoff fitness compared to the average payoff fitness. However, the difference between the two functions decreases as the average degree increases. As the average degree increases, cooperation decreases for the accumulated payoff fitness, while it increases for the average payoff fitness. Moreover, for the average payoff fitness, low-degree nodes play a more important role in spreading cooperative strategies than for the accumulated payoff fitness.

scholarly journals Dynamics analysis of an online gambling spreading model on scale-free networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yu Kong ◽  
Tao Li ◽  
Yuanmei Wang ◽  
Xinming Cheng ◽  
He Wang ◽  
...  
Keyword(s):  
Network Topology ◽  
Negative Impact ◽  
Online Gambling ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Scale Free ◽  
Spreading Model ◽  
Spreading Dynamics ◽  
Scale Free Networks ◽  
Gambling Policy

AbstractNowadays, online gambling has a great negative impact on the society. In order to study the effect of people’s psychological factors, anti-gambling policy, and social network topology on online gambling dynamics, a new SHGD (susceptible–hesitator–gambler–disclaimer) online gambling spreading model is proposed on scale-free networks. The spreading dynamics of online gambling is studied. The basic reproductive number $R_{0}$ R 0 is got and analyzed. The basic reproductive number $R_{0}$ R 0 is related to anti-gambling policy and the network topology. Then, gambling-free equilibrium $E_{0}$ E 0 and gambling-prevailing equilibrium $E_{ +} $ E + are obtained. The global stability of $E_{0}$ E 0 is analyzed. The global attractivity of $E_{ +} $ E + and the persistence of online gambling phenomenon are studied. Finally, the theoretical results are verified by some simulations.

scholarly journals Effective gravitation path routing strategy on scale-free networks

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Jinlong Ma ◽  
Junfeng Zhang ◽  
Yongqiang Zhang
Keyword(s):  
Scale Free ◽  
Routing Strategy ◽  
Scale Free Networks
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