a new spatial index structure for efficient query processing in location based services
DESCRIPTION
A New Spatial Index Structure for Efficient Query Processing in Location Based Services. Speaker : Yihao Jhang Adviser: Yuling Hsueh. 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing. Outline. Introduction Related work Grid Index B + -tree - PowerPoint PPT PresentationTRANSCRIPT
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A New Spatial Index Structure for Efficient Query Processing in Location Based Services
Speaker: Yihao JhangAdviser: Yuling Hsueh
2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing
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Outline• Introduction• Related work
– Grid Index– B+-tree
• ISGrid• Query Processing• Experiment• Conclusion
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Introduction• A new spatial index structure.• ISGrid provides better efficient query
processing than R-tree.• ISGrid is a grid structure that
provides direct accesses to data and uses Minimum Boundary Rectangle(MBR) as a leaf node.
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Grid index• Grid is a regular tessellation of a 2-D surface
that divides it into a series of contiguous cells, which can then be assigned unique identifiers and used for spatial indexing purposes.
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B+-tree• B+-tree is a tree structure. It usually
employed in database or file operating system.
• It has the link to point to the closer data and allow quick sequence read the data.
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ISGrid• Configuration of ISGrid
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ISGrid(cont.)
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ISGrid(cont.)• How to choose neighbor nodes?
– Traditional: the order of the distance. (x)– Best method: Voronoi Diagram
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Query Processing• k-NN Queries
– STEP 1: Searching the nearest leaf node to the query point using the grid index.
– STEP 2: Searching the k-NNs through visiting the neighbor node entry.
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Query Processing(cont.)
STEP1
STEP2
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Query Processing(cont.)• Range Queries
– STEP1: Searching the nearest leaf node to the query point using the grid index.
– STEP2: Searching the objects within a certain range using the neighbor node information.
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Query Processing(cont.)
STEP1
STEP2
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Experiment• Performance of k-NN query
processing.
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Experiment(cont.)• Performance of continuous k-NN by
CNNS.
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Conclusions• Authors proposed an index structure,
called ISGrid.• ISGrid provides efficient continuous
k-NN query processing in the environment for static objects and moving queries.
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Thank you for Listening!