Periodic Patterns in Human Encounters

627b1a10da6bd579fd7f2ea8c73774b8?s=47 Matt J Williams
May 01, 2011
30

Periodic Patterns in Human Encounters

Research talk.
Venue: Research Retreat, Cardiff University School of Computer Science & Informatics.

627b1a10da6bd579fd7f2ea8c73774b8?s=128

Matt J Williams

May 01, 2011
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Transcript

  1. | Research Retreat | May 2011 | Matt Williams CS&I

    Research Retreat May 2011
  2. | Research Retreat | May 2011 | Periodic Patterns in

    Human Encounters Matt Williams CS&I Research Retreat May 2011
  3. | Research Retreat | May 2011 | Human encounters

  4. | Research Retreat | May 2011 | Why study human

    encounters? opportunistic content sharing virus spreading patterns
  5. | Research Retreat | May 2011 | Periodicity and patterns

    in human encounters
  6. | Research Retreat | May 2011 | • How prevalent

    are periodic encounter patterns in human networks? • How does the presence of periodic encounters affect information flow? • Can periodic patterns be detected and used to improve content sharing in opportunistic networks? Research questions
  7. | Research Retreat | May 2011 | How do we

    study human encounters? Smartphone Bluetooth encounters (@MIT) WiFi access point visits (@Dartmouth Campus) Foursquare venue visits (@Cardiff +others)
  8. | Research Retreat | May 2011 | How do we

    study human encounters? Smartphone Bluetooth encounters (@MIT) WiFi access point visits (@Dartmouth Campus) Foursquare venue visits (@Cardiff +others)
  9. | Research Retreat | May 2011 | • A group

    of nodes that regularly encounter one another with a given period Periodic encounter communities (PECs)
  10. | Research Retreat | May 2011 | • In opportunistic

    networks, a decentralised algorithm is needed Detecting PECs in OppNets
  11. | Research Retreat | May 2011 | Detecting PECs in

    OppNets
  12. | Research Retreat | May 2011 | • Period: the

    gap between reappearances of the community (24 hrs, 7 days, etc.) • Diameter: the distance between the most distant nodes in the community Properties of PECs diameter = 4
  13. | Research Retreat | May 2011 |

  14. | Research Retreat | May 2011 | • Diameter and

    period give us a theoretical worst-case for the time needed for all nodes to send messages to each other • In practice, how does information sharing compare to the worst-case? Information sharing
  15. | Research Retreat | May 2011 | in 75% of

    PECs, information sharing took less than 1/2 the worst-case time
  16. | Research Retreat | May 2011 | • PEC detection

    relies on a crisp definition • Inherent uncertainty in encounter times poses a problem Limitations
  17. | Research Retreat | May 2011 | • Dealing with

    fuzziness: borrow a technique from neuroscience! • Spike train synchrony: measures the similarity of bursting patterns of neurons Ongoing work: spike train methods Kreuz et al. 2009
  18. | Research Retreat | May 2011 | Human encounter ‘trains’

    Week 1 Week 2 Week 4 Week 3
  19. | Research Retreat | May 2011 | Human encounter ‘trains’

    Week 1 Week 2 Week 4 Week 3
  20. | Research Retreat | May 2011 | Regions of regularity

    Kreuz et al. 2009
  21. | Research Retreat | May 2011 | • Periodic encounter

    patterns exist and can be automatically detected • Evidence that periodic encounter patterns influence information flows in human encounter networks • Spike train methods are a promising solution for the detection of ‘fuzzy’ encounter patterns Summary Thanks for listening!
  22. | Research Retreat | May 2011 | References M.J. Williams,

    R.M. Whitaker, S.M. Allen, Decentralised detection of periodic encounter communities in opportunistic networks, Ad Hoc Networks, 10.1016/j.adhoc.2011.07.008. T. Kreuz, D. Chicharro, R. G. Andrzejak, J. S. Haas, and H. D. I. Abarbanel, Measuring multiple spike train synchrony, Journal of Neuroscience Methods, vol. 183, no. 2, pp. 287–299, 2009. Attribution Library Courtyard. nevolution. http://www.flickr.com/photos/nevolution/ 2906377551/