ABSTRACT
Community is an important attribute of Pocket Switched Networks (PSNs), since mobile devices are carried by people who tend to belong to communities in their social life. We discover the heterogeneity of human interactions such as community formation from real world human mobility traces. We have introduced novel distributed community detection approaches and evaluated with those traces [11]. This paper describes a series of visualizations to show characteristics of human mobility traces including community detection. We focus on extracting information related to levels of clustering, network transitivity, and strong community structure. The progression of the connection map along the community formation process is also visualized.
- Wireless Rope, http://sourceforge.net/projects/wirelessrope, 2006.Google Scholar
- A. Chaintreau et al. Impact of human mobility on the design of opportunistic forwarding algorithms. In Proc. INFOCOM, April 2006.Google ScholarCross Ref
- A. Clauset. Finding local community structure in networks. Physical Review E, 72:026132, 2005.Google ScholarCross Ref
- D. College. A community resource for archiving wireless data at dartmouth, http://crawdad.cs.dartmouth.edu/index.php, 2007.Google Scholar
- L. Danon, J. Duch, A. Diaz-Guilera, and A. Arenas. Comparing community structure identification, 2005.Google Scholar
- C. Diot et al. Haggle Project, http://www.haggleproject.org, 2004.Google Scholar
- N. Eagle and A. Pentland. Reality mining: sensing complex social systems. Personal and Ubiquitous Computing, V10(4):255--268, May 2006. Google ScholarDigital Library
- K. Fall. A delay-tolerant network architecture for challenged internets. In Proc. SIGCOMM, 2003. Google ScholarDigital Library
- P. Hui and J. Crowcroft. Bubble rap: Forwarding in small world dtns in every decreasing circles. Technical Report UCAM-CL-TR684, Univ. of Cambridge, 2007.Google Scholar
- P. Hui and J. Crowcroft. How small lables create big improvements. In Proc. IEEE ICMAN, March 2007. Google ScholarDigital Library
- P. Hui, E.Yoneki, S. Chan, and J. Crowcroft. Distributed community detection in delay tolerant networks. In Proc. MobiArch, 2007. Google ScholarDigital Library
- M. E. J.Newman. Analysis of weighted networks. Physical Review E, 70:056131, 2004.Google ScholarCross Ref
- M. Newman. Detecting community structure in networks. Eur. Phys. J. B, 38:321--330, 2004.Google ScholarCross Ref
- T. Nicolai, E. Yoneki, N. Behrens, and H. Kenn. Exploring social context with the wireless rope. In Proc. Workshop MONET: LNCS 4277, 2006. Google ScholarDigital Library
- G. Palla et al. Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043):814--818, 2005.Google ScholarCross Ref
- UCSD. Wireless topology discovery project, http://sysnet.ucsd.edu/wtd/wtd.html, 2004.Google Scholar
Index Terms
- Visualizing community detection in opportunistic networks
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