Edges Immunization Strategy Based on Discrete PSO in Weighted Scale-Free Network

2012 ◽  
Author(s):  
Bing Lin ◽  
Wenzhong Guo ◽  
Guolong Chen
Keyword(s):  
Scale Free Network ◽  
Immunization Strategy ◽  
Scale Free ◽  
Free Network ◽  
Discrete Pso

Greedy immunization strategy in weighted scale-free networks

2014 ◽  
Vol 31 (8) ◽  
pp. 1627-1634 ◽  
Author(s):  
Zhang-Hui Liu ◽  
Guo-Long Chen ◽  
Ning-Ning Wang ◽  
Biao Song
Keyword(s):  
Greedy Algorithm ◽  
Design Methodology ◽  
Experimental Results ◽  
Scale Free Network ◽  
Immunization Strategy ◽  
Content Type ◽  
Network Partition ◽  
Scale Free ◽  
Scale Free Networks ◽  
Free Network

Purpose – The purpose of this paper is to present a new immunization strategy for effectively solving the control of the spread of the virus. Design/methodology/approach – Inspired by the idea of network partition, taking two optimization targets which are the scale of sub-network and the sum of the strengths of the sub-network's nodes into account at the same time, a new immunization strategy based on greedy algorithm in the scale-free network is presented. After specifying the number of nodes through the immunization, the network is divided into the scale of sub-network and the sum of the strength of the sub-network's nodes as small as possible. Findings – The experimental results show that the proposed algorithm has the better performance than targeted immunization which is supposed to be highly efficient at present. Originality/value – This paper proposes a new immunization strategy based on greedy algorithm in the scale-free network for effectively solving the control of the spread of the virus.

Multi-granularity immunization strategy based on SIRS model in scale-free network

2015 ◽  
Vol 29 (08) ◽  
pp. 1550023 ◽  
Author(s):  
Fuzhong Nian ◽  
Ke Wang
Keyword(s):  
Warning Signal ◽  
Threshold Value ◽  
Scale Free Network ◽  
Epidemic Outbreak ◽  
Epidemic Spreading ◽  
Immunization Strategy ◽  
Scale Free ◽  
Sirs Model ◽  
Free Network ◽  
Spreading Rates

In this paper, a new immunization strategy was established to prevent the epidemic spreading based on the principle of "Multi-granularity" and "Pre-warning Mechanism", which send different pre-warning signal with the risk rank of the susceptible node to be infected. The pre-warning means there is a higher risk that the susceptible node is more likely to be infected. The multi-granularity means the susceptible node is linked with multi-infected nodes. In our model, the effect of the different situation of the multi-granularity immunizations is compared and different spreading rates are adopted to describe the epidemic behavior of nodes. In addition the threshold value of epidemic outbreak is investigated, which makes the result more convincing. The theoretical analysis and the simulations indicate that the proposed immunization strategy is effective and it is also economic and feasible.

Research on new evolution model of scale-free network

2009 ◽  
Vol 29 (5) ◽  
pp. 1230-1232
Author(s):  
Hao RAO ◽  
Chun YANG ◽  
Shao-hua TAO
Keyword(s):  
Evolution Model ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network

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.

The Barabási and Albert scale-free network model

2018 ◽  
Vol 35 (1) ◽  
pp. 123-132 ◽  
Author(s):  
Lei Zhu ◽  
Lei Wang ◽  
Xiang Zheng ◽  
Yuzhang Xu
Keyword(s):  
Network Model ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network
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