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1
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
2
Outline
• Introduction• Related work
– Grid Index– B+-tree
• ISGrid• Query Processing• Experiment• Conclusion
3
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!