Detecting dynamic communities in opportunistic networks

  • Authors:
  • Kuang Xu;Guang-Hua Yang;Victor O. K.Li;Shu-Yan Chan

  • Affiliations:
  • The University of Hong Kong;The University of Hong Kong;The University of Hong Kong;University of Cambridge

  • Venue:
  • ICUFN'09 Proceedings of the first international conference on Ubiquitous and future networks
  • Year:
  • 2009

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Abstract

In opportunistic networks, communities of mobile entities may be utilized to improve the efficiency of message forwarding. However, identifying communities that are dynamically changing in mobile environment is non-trivial. Based on random walk on graphs, in this paper we present a community detection algorithm that takes into account the aging and weight of contacts between mobile entities. Our idea originates from message-forwarding operations in opportunistic networks. We evaluate the algorithm on both computer-generated networks and real-world human mobility traces. The result shows that our proposed algorithm can find the communities and detect the changes in their structures over time.