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Improved targeted immunization strategies based on two rounds of selection.

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Title: Improved targeted immunization strategies based on two rounds of selection.
Authors: Xia, Ling-Ling1,2, Song, Yu-Rong1 songyr@njupt.edu.cn, Li, Chan-Chan1, Jiang, Guo-Ping1
Source: Physica A. Apr2018, Vol. 496, p540-547. 8p.
Subjects: Immunization, Problem solving, Betweenness relations (Mathematics), Simulation methods & models, Parameter estimation
Abstract: In the case of high degree targeted immunization where the number of vaccine is limited, when more than one node associated with the same degree meets the requirement of high degree centrality, how can we choose a certain number of nodes from those nodes, so that the number of immunized nodes will not exceed the limit? In this paper, we introduce a new idea derived from the selection process of second-round exam to solve this problem and then propose three improved targeted immunization strategies. In these proposed strategies, the immunized nodes are selected through two rounds of selection, where we increase the quotas of first-round selection according the evaluation criterion of degree centrality and then consider another characteristic parameter of node, such as node’s clustering coefficient, betweenness and closeness, to help choose targeted nodes in the second-round selection. To validate the effectiveness of the proposed strategies, we compare them with the degree immunizations including the high degree targeted and the high degree adaptive immunizations using two metrics: the size of the largest connected component of immunized network and the number of infected nodes. Simulation results demonstrate that the proposed strategies based on two rounds of sorting are effective for heterogeneous networks and their immunization effects are better than that of the degree immunizations. [ABSTRACT FROM AUTHOR]
Copyright of Physica A is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 127842770
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Improved targeted immunization strategies based on two rounds of selection.
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  Data: <searchLink fieldCode="AR" term="%22Xia%2C+Ling-Ling%22">Xia, Ling-Ling</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Song%2C+Yu-Rong%22">Song, Yu-Rong</searchLink><relatesTo>1</relatesTo><i> songyr@njupt.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Chan-Chan%22">Li, Chan-Chan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Jiang%2C+Guo-Ping%22">Jiang, Guo-Ping</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Physica+A%22">Physica A</searchLink>. Apr2018, Vol. 496, p540-547. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Immunization%22">Immunization</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink><br /><searchLink fieldCode="DE" term="%22Betweenness+relations+%28Mathematics%29%22">Betweenness relations (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink>
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  Data: In the case of high degree targeted immunization where the number of vaccine is limited, when more than one node associated with the same degree meets the requirement of high degree centrality, how can we choose a certain number of nodes from those nodes, so that the number of immunized nodes will not exceed the limit? In this paper, we introduce a new idea derived from the selection process of second-round exam to solve this problem and then propose three improved targeted immunization strategies. In these proposed strategies, the immunized nodes are selected through two rounds of selection, where we increase the quotas of first-round selection according the evaluation criterion of degree centrality and then consider another characteristic parameter of node, such as node’s clustering coefficient, betweenness and closeness, to help choose targeted nodes in the second-round selection. To validate the effectiveness of the proposed strategies, we compare them with the degree immunizations including the high degree targeted and the high degree adaptive immunizations using two metrics: the size of the largest connected component of immunized network and the number of infected nodes. Simulation results demonstrate that the proposed strategies based on two rounds of sorting are effective for heterogeneous networks and their immunization effects are better than that of the degree immunizations. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Physica A is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.physa.2017.12.017
    Languages:
      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 540
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      – SubjectFull: Immunization
        Type: general
      – SubjectFull: Problem solving
        Type: general
      – SubjectFull: Betweenness relations (Mathematics)
        Type: general
      – SubjectFull: Simulation methods & models
        Type: general
      – SubjectFull: Parameter estimation
        Type: general
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      – TitleFull: Improved targeted immunization strategies based on two rounds of selection.
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            NameFull: Xia, Ling-Ling
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            NameFull: Song, Yu-Rong
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            NameFull: Li, Chan-Chan
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            NameFull: Jiang, Guo-Ping
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            – D: 15
              M: 04
              Text: Apr2018
              Type: published
              Y: 2018
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              Value: 496
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