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Leader Nodes in Communities for Information Spreading

  • Natalia M. Markovich
  • , Maxim S. Ryzhov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The paper is devoted to the effective information spreading in random complex networks. Our objective is to elect leader nodes or communities of the network, which may spread the content among all nodes faster. We consider a well-known SPREAD algorithm by Mosk-Aoyama and Shah (2006), which provides the spreading and the growth of the node set possessing the information. Assuming that all nodes have asynchronous clocks, the next node is chosen uniformly among nodes of the network by the global clock tick according to a Poisson process. The extremal index measures the clustering tendency of high threshold exceedances. The node extremal index shows the ability to attract highly ranked nodes in the node orbit. Considering a closeness centrality as a measure of a node’s leadership, we find the relation between its extremal index and the minimal spreading time.

Original languageEnglish
Title of host publicationDistributed Computer and Communication Networks - 23rd International Conference, DCCN 2020, Revised Selected Papers
EditorsVladimir M. Vishnevskiy, Dmitry V. Kozyrev, Konstantin E. Samouylov, Dmitry V. Kozyrev
PublisherSpringer Science and Business Media Deutschland GmbH
Pages475-484
Number of pages10
ISBN (Print)9783030664701
DOIs
StatePublished - 1 Jan 2020
Externally publishedYes
Event23rd International Conference on Distributed Computer and Communication Networks, DCCN 2020 - Moscow, Russian Federation
Duration: 14 Sep 202018 Sep 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12563 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Distributed Computer and Communication Networks, DCCN 2020
Country/TerritoryRussian Federation
CityMoscow
Period14/09/2018/09/20

Keywords

  • Community
  • Complex network
  • Extremal index
  • Information spreading
  • Random graph

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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