A distributed immunization strategy based on autonomy-oriented computing

Jiming LIU; Chao Gao; Ning Zhong

doi:10.1007/978-3-642-04125-9_53

A distributed immunization strategy based on autonomy-oriented computing

Jiming LIU^*, Chao Gao, Ning Zhong

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

4 Citations (Scopus)

Abstract

In recent years, immunization strategies have been developed for stopping epidemics in complex-network-like environments. So far, it remains to be difficult for the existing strategies to deal with distributed community networks, even though they are ubiquitous in the real world. In this paper, we propose a distributed immunization strategy based on the ideas of self-organization and positive feedback from Autonomy-Oriented Computing (AOC). The AOC-based strategy can effectively be applied to handle large-scale, dynamic networks. Our experimental results have shown that the autonomous entities deployed in this strategy can collectively find and immunize most of the highly-connected nodes in a network within just a few steps.

Original language	English
Title of host publication	Foundations of Intelligent Systems - 18th International Symposium, ISMIS 2009, Proceedings
Pages	503-512
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-04125-9_53
Publication status	Published - 2009
Event	18th International Symposium on Methodologies for Intelligent Systems, ISMIS 2009 - Prague, Czech Republic Duration: 14 Sept 2009 → 17 Sept 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5722 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Symposium on Methodologies for Intelligent Systems, ISMIS 2009
Country/Territory	Czech Republic
City	Prague
Period	14/09/09 → 17/09/09

Scopus Subject Areas

Theoretical Computer Science
Computer Science(all)

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10.1007/978-3-642-04125-9_53

Cite this

LIU, J., Gao, C., & Zhong, N. (2009). A distributed immunization strategy based on autonomy-oriented computing. In Foundations of Intelligent Systems - 18th International Symposium, ISMIS 2009, Proceedings (pp. 503-512). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5722 LNAI). https://doi.org/10.1007/978-3-642-04125-9_53

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title = "A distributed immunization strategy based on autonomy-oriented computing",

abstract = "In recent years, immunization strategies have been developed for stopping epidemics in complex-network-like environments. So far, it remains to be difficult for the existing strategies to deal with distributed community networks, even though they are ubiquitous in the real world. In this paper, we propose a distributed immunization strategy based on the ideas of self-organization and positive feedback from Autonomy-Oriented Computing (AOC). The AOC-based strategy can effectively be applied to handle large-scale, dynamic networks. Our experimental results have shown that the autonomous entities deployed in this strategy can collectively find and immunize most of the highly-connected nodes in a network within just a few steps.",

author = "Jiming LIU and Chao Gao and Ning Zhong",

note = "Copyright: Copyright 2009 Elsevier B.V., All rights reserved.; 18th International Symposium on Methodologies for Intelligent Systems, ISMIS 2009 ; Conference date: 14-09-2009 Through 17-09-2009",

year = "2009",

doi = "10.1007/978-3-642-04125-9_53",

language = "English",

isbn = "3642041248",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "503--512",

booktitle = "Foundations of Intelligent Systems - 18th International Symposium, ISMIS 2009, Proceedings",

}

LIU, J, Gao, C & Zhong, N 2009, A distributed immunization strategy based on autonomy-oriented computing. in Foundations of Intelligent Systems - 18th International Symposium, ISMIS 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5722 LNAI, pp. 503-512, 18th International Symposium on Methodologies for Intelligent Systems, ISMIS 2009, Prague, Czech Republic, 14/09/09. https://doi.org/10.1007/978-3-642-04125-9_53

A distributed immunization strategy based on autonomy-oriented computing. / LIU, Jiming; Gao, Chao; Zhong, Ning.
Foundations of Intelligent Systems - 18th International Symposium, ISMIS 2009, Proceedings. 2009. p. 503-512 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5722 LNAI).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AB - In recent years, immunization strategies have been developed for stopping epidemics in complex-network-like environments. So far, it remains to be difficult for the existing strategies to deal with distributed community networks, even though they are ubiquitous in the real world. In this paper, we propose a distributed immunization strategy based on the ideas of self-organization and positive feedback from Autonomy-Oriented Computing (AOC). The AOC-based strategy can effectively be applied to handle large-scale, dynamic networks. Our experimental results have shown that the autonomous entities deployed in this strategy can collectively find and immunize most of the highly-connected nodes in a network within just a few steps.

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LIU J, Gao C, Zhong N. A distributed immunization strategy based on autonomy-oriented computing. In Foundations of Intelligent Systems - 18th International Symposium, ISMIS 2009, Proceedings. 2009. p. 503-512. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-04125-9_53

A distributed immunization strategy based on autonomy-oriented computing

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