Community detection in weighted networks: Algorithms and applications

Zongqing Lu, Yonggang Wen, Guohong Cao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

50 Scopus citations

Abstract

Community detection is an important issue due to its wide use in designing network protocols such as data forwarding in Delay Tolerant Networks (DTN) and worm containment in Online Social Networks (OSN). However, most of the existing community detection algorithms focus on binary networks. Since most networks are weighted such as social networks, DTN or OSN, in this paper, we address the problems of community detection in weighted networks and exploit community for data forwarding in DTN and worm containment in OSN. We propose a novel community detection algorithm, and then introduce two metrics called intra-centrality and inter-centrality, to characterize nodes in communities. Based on these metrics, we propose an efficient data forwarding algorithm for DTN and an efficient worm containment strategy for OSN. Extensive trace-driven simulation results show that the data forwarding algorithm and the worm containment strategy significantly outperform existing works.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Pervasive Computing and Communications, PerCom 2013
Pages179-184
Number of pages6
DOIs
StatePublished - Jul 18 2013
Event11th IEEE International Conference on Pervasive Computing and Communications, PerCom 2013 - San Diego, CA, United States
Duration: Mar 18 2013Mar 22 2013

Publication series

Name2013 IEEE International Conference on Pervasive Computing and Communications, PerCom 2013

Other

Other11th IEEE International Conference on Pervasive Computing and Communications, PerCom 2013
Country/TerritoryUnited States
CitySan Diego, CA
Period3/18/133/22/13

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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