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Avatar Mobility in Wei Tsang Ooi Mehul Motani Huiguang Liang Ian - PowerPoint PPT Presentation

Avatar Mobility in Wei Tsang Ooi Mehul Motani Huiguang Liang Ian Tay Ming Feng Neo National University of Singapore avatar mobility: who is where, when why do we care? research in systems support for NVE how to partition a world into


  1. Avatar Mobility in Wei Tsang Ooi Mehul Motani Huiguang Liang Ian Tay Ming Feng Neo National University of Singapore

  2. avatar mobility: who is where, when

  3. why do we care?

  4. research in systems support for NVE

  5. how to partition a world into cells and assign cells to servers considering - interaction across cells - movement across cells - avatar density in each cell :

  6. how to predict avatar movement (and therefore what a user will see next)?

  7. AoI-based scheme

  8. how many connections? how stable are the connections?

  9. supernode-based scheme

  10. how to pick supernodes? how stable are the supernodes?

  11. how to simulate avatar mobility?

  12. random walk random waypoint clustered movement :

  13. or, small-scale implementation

  14. no large-scale NVE available until recently

  15. “My life is so great that I literally wanted a second one!” - Dwight Schrute, The Office

  16. 256x256 m regions.

  17. 470,478 residents logged in between 12-19 June 2008

  18. secondlife.com/whatis/economy-graphs.php

  19. • collect mobility traces of avatars in Second Life • what it means w.r.t. systems design for NVEs?

  20. Trace Collection

  21. FPS MMORPG NVE

  22. Linden, can we get access to the server traces? No.

  23. • Wrote our own client • Parses packets using libsecondlife • Insert bots into regions • Log positions of avatars every 10s

  24. who is where, when (doing what)

  25. Isis: number of visits to a cell

  26. caching/prefetching based on popularity of locations?

  27. Isis: average pause time in a cell

  28. pick supernodes from sticky location?

  29. Isis: average speed in a cell

  30. mobility model: random walk + pathway ?

  31. Reasonably high churn (up to 6/min)

  32. 1 min 10 min 1 hr 2 hr Highly skewed. Some stay for hours.

  33. can not pick supernodes uniformly

  34. meeting : encounter between two avatars (within each other AoI)

  35. 1 min 1 hr 10 min 2 hr Most meetings are short.

  36. Meeting size is large.

  37. high overhead in maintaining AoI neighbors

  38. • very little temporal variations (predictable) • avatars rotates 18 % of time (SL’s prefetching is wasteful) • 25-35 % revisits regions within a day (region-based caching?)

  39. understanding how real avatars move is key to design and evaluation of NVEs.

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