Spatiotemporal Data Indexing

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Spatiotemporal Data Indexing

• Presented by Slobodan Rasetic
• University of Alberta

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Spatiotemporal Data

• Spatiotemporal data in its most general form
  consists of observations with their timestamps
  and spatial location.
• Trajectories are often used to represent moving
  objects.
• In this case, the positions of moving objects are
  recorded at discrete points in time, and a linear
  interpolation between two successive locations is
  typically assumed
• Practical examples of useful spatio-temporal
  data include GPS, wireless networks, and sensor
  data.

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Spatiotemporal Data (cont)
Moving object trajectory Pfo00
Moving object trajectories Pfo00
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Modeling Spatiotemporal Data

• The main problem towards modeling spatiotemporal
  data is that it needs to be modeled in a manner
  which best supports a particular user query.
• There are several types of users queries that can
  be posed over spatiotemporal data.
• Examples of such include range queries and
  nearest neighbor queries.

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R-Trees

• R-Tree based structures provide a good mechanism
  for supporting a wide range of query types for
  Spatiotemporal data.
• Spatial-temporal data, like spatial data can be
  approximated using a Minimum Bounding Rectangle
  (MBB).

Approximation of Spatial Data Gut84
A resulting R-Tree Structure Gut84
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R-Trees (Cont)

• Approximating trajectories using MBBs and using
  an R-Tree based structure for query support has
  the following benefits
• 1. Low storage overhead.
• 2. Low computational overhead to answer user
  queries.
• Approximating trajectories using R-Tree based
  structures has the drawback of introducing a
  great deal of dead space.
• This dead space can be reduced by dividing
  trajectories into smaller segments and
  approximating their sub components.

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Trajectory Approximation

• Using courser approximations for trajectories has
  the obvious benefit of using less dead space.
• Too much dead space leads to poor query
  performance, i.e. query miss hits.

Reducing the dead space occupied by a trajectory
Pfo00
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Query Performance

• Splitting a trajectory without reference to a
  particular query size might also lead to poor
  query performance.
• The following examples helps to describe why this
  is true.

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References

• Gut84 GUTTMAN, A. R-trees a Dynamic Index
  Structure for Spatial Searching. In Proc. of
  ACM-SIGMOD Conference on the Management of Data,
  pp. 47-57, 1984.
• Pfo00 PFOSER, D., JENSEN, C. S., AND
  THEODORIDIS, Y.Novel Approaches in Query
  Processing for Moving Object Trajectories. In
  Proceedings of the 26st VLDB Conf. (Cairo,Egypt,
  September 2000), pp. 395406.

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Questions and Discussion??