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Epidemic propagation on adaptive coevolutionary networks with preferential local-world reconnecting strategy.

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Title: Epidemic propagation on adaptive coevolutionary networks with preferential local-world reconnecting strategy.
Authors: Song Yu-Rong1 songyr@njupt.edu.cn, Jiang Guo-Ping1, Gong Yong-Wang1
Source: Chinese Physics B. 2013, Vol. 22 Issue 4, p1-7. 7p.
Subjects: Cellular automata, Coevolution, Optical bistability, Computer network security, Sequential machine theory, Mathematical models
Abstract: In the propagation of an epidemic in a population, individuals adaptively adjust their behavior to avoid the risk of an epidemic. Differently from existing studies where new links are established randomly, a local link is established preferentially in this paper. We propose a new preferentially reconnecting edge strategy depending on spatial distance (PR- SD). For the PR-SD strategy, the new link is established at random with probability p and in a shortest distance with the probability 1 - p. We establish the epidemic model on an adaptive network using Cellular Automata, and demonstrate the effectiveness of the proposed model by numerical simulations. The results show that the smaller the value of parameter p, the more difficult the epidemic spread is. The PR-SD strategy breaks long-range links and establishes as many short-range links as possible, which causes the network efficiency to decrease quickly and the propagation of the epidemic is restrained effectively. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:In the propagation of an epidemic in a population, individuals adaptively adjust their behavior to avoid the risk of an epidemic. Differently from existing studies where new links are established randomly, a local link is established preferentially in this paper. We propose a new preferentially reconnecting edge strategy depending on spatial distance (PR- SD). For the PR-SD strategy, the new link is established at random with probability p and in a shortest distance with the probability 1 - p. We establish the epidemic model on an adaptive network using Cellular Automata, and demonstrate the effectiveness of the proposed model by numerical simulations. The results show that the smaller the value of parameter p, the more difficult the epidemic spread is. The PR-SD strategy breaks long-range links and establishes as many short-range links as possible, which causes the network efficiency to decrease quickly and the propagation of the epidemic is restrained effectively. [ABSTRACT FROM AUTHOR]
ISSN:16741056
DOI:10.1088/1674-1056/22/4/040205