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An overlapping community detection algorithm for opportunistic networks

  • Inner Mongolia University

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

Abstract

A more detailed community structure can contribute to a better understanding of the network, which can also benefit efficient routing protocols and QoS schemes designing. For an Opportunistic Network which consists of different kinds of mobile nodes, its topology changes over time. Therefore the community detection becomes more difficult than static situations. Moreover the overlapping community detection is a more complex problem. This paper analyzes the time varying topology of Opportunistic Networks and the overlapping community structures of human. Then, we propose a new detection algorithm to solve the overlapping community detection problems in Opportunistic Networks. Only with the local network topology information and a short period, nodes can get their overlapping community structures by our detection algorithm. Numerical simulations with both scenarios of movement models and real trace data are presented to illustrate the accuracy and efficiency of our algorithm.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE Computers, Communications and IT Applications Conference, ComComAp 2014
EditorsZhangbing Zhou, Jianwei Niu, Lei Shu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages110-115
Number of pages6
ISBN (Electronic)9781479948116
DOIs
StatePublished - 20 Jan 2014
Externally publishedYes
Event2014 IEEE Computers, Communications and IT Applications Conference, ComComAp 2014 - Beijing, China
Duration: 20 Oct 201422 Oct 2014

Publication series

NameProceedings - 2014 IEEE Computers, Communications and IT Applications Conference, ComComAp 2014

Conference

Conference2014 IEEE Computers, Communications and IT Applications Conference, ComComAp 2014
Country/TerritoryChina
CityBeijing
Period20/10/1422/10/14

Keywords

  • community detection
  • Opportunistic Networks
  • overlapping communities
  • simulation
  • social relationships

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