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Novel Approaches to the Indexing of Moving Object Trajectories

Novel Approaches to the Indexing of Moving Object Trajectories. Presented by YuQing Zhang. Dieter Pfoser Christian S. Jensen Yannis Theodoridis. 7. 6. 2. 3. 8. 1. 4. 5. Performance Comparison. Introduction. Moving Objects. Access Methods. Strength and Weakness.

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Novel Approaches to the Indexing of Moving Object Trajectories

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  1. Novel Approaches to the Indexing of Moving Object Trajectories Presented by YuQing Zhang Dieter Pfoser Christian S. Jensen Yannis Theodoridis

  2. 7 6 2 3 8 1 4 5 Performance Comparison Introduction Moving Objects Access Methods Strength and Weakness Query Processing Conclusion and Future Works Relate to My Project Contents AAU

  3. Methods Spatio-Temporal R-Tree (STR-tree) Trajectory-Bundle Tree (TB-tree) Introduction • Objects in Real World • Space • Time • Preservation of trajectories • Line segments belong to the same trajectory • With respect to time • Access Methods AAU

  4. 1 2 Simply Store the position samples Linear Interpolation Moving Object • Trajectories • How to represent the movements of objects AAU

  5. Moving Objects • Trajectories • Spatiotemporal Workspace • Temporal Dimension AAU

  6. Moving Objects • Queries • Coordinate-based Queries: point, range and nearest neighbor Example: Find all buses within AAU during 8.00AM - 9.00PM • Trajectory-based Queries • Topological Queries : important but expensive Example: Whether the BUS 17 entered AAU at 8.00AM • Navigation Queries: speed or heading Example: What is Bus 17’s top speed? • Combined Queries • Example: What were the trajectories of buses after they left AAU between 7am-8am today in the next hour? AAU

  7. Access Methods --- R tree • What is R-tree • Height balanced tree • Index records in leaf nodes • Pointer to actual data • Inefficiencies of R-tree • Dead Space • Hard to determine a line segment belongs to AAU

  8. Access Methods --- STR-tree • Difference with R-tree Insertion/split Strategy • Insertion Strategy • Not only spatial closeness, but also trajectory preservation • R-tree: least enlargement criterion • STR-tree: keep line segments belong to the same trajectory • Insertion Algorithm • FindNode() • Preservation parameter AAU

  9. Quadratic Spilt Algorithm a 1 2 3 Disconnected segments Bi-connected segments Forward (backward) Connected segments The disconnected segments are placed into the newly created node. b The most recent backward-connected segment is placed into the newly created node. c Access Methods --- STR-tree • Spilt Strategy • General idea: put newer and thus more recent segments into new nodes • A node can contain: AAU

  10. Access Methods --- TB-tree • Take a radical step • Concession: node overlap or spatial discrimination AAU

  11. Access Methods --- TB-tree • Insertion Algorithm Goal: cut the whole trajectory of a moving object into pieces AAU

  12. Access Methods --- TB-tree • Trajectory Preservation • A double linked List: preserves trajectory evolution simple solution to retrieve segments based on trajectory identifier AAU

  13. Query Processing • Combined Search in the R-tree and STR-tree • retrieve an initial set of segments based on a spatiotemporal range • extract partial trajectories • not retrieving the same trajectory twice 3 4 AAU

  14. Query Processing • Combined Search in the TB-tree • the difference lies in how the partial trajectories are retrieved the linked list allow us to retrieve connected segments without searching • two possibilities: a connected segment can be in the same leaf node or in another node • Same: finding it is trivial • Another: follow the pointer AAU

  15. Performance comparison • Datasets • GSTD generator • Space Utilization and Index Size • Space Utilization: R-tree is the smallest • Index size: R-tree is the biggest TB-tree is smaller than that of STR-tree AAU

  16. Performance comparison • Summary AAU

  17. Conclusion and Future Work • Conclusion • presents a set of pure spatiotemporal queries • trajectory-based queries • combined queries • Shortcomings of R-tree • STR-tree TB-tree STR-tree performance stays behind the TB-tree AAU

  18. Conclusion and Future Work • Future Work • Refine navigational and topological queries more detail. • Pay attention to some expensive spatial queries. • Investigating geometric shapes other than MBBs as approximations for moving objects’ trajectories deserves further research AAU

  19. Relate to my Project • My project • Range queries • Use Oracle • Maybe… • Give another view of questions AAU

  20. Strength and weakness • Strength • Describe each method quite clearly • Use some comparison • Some figures are helpful AAU

  21. Strong and weakness • Weakness • No Related Work introduction • Some parameters in some algorithms are ambiguous • Reader must have the knowledge of R-tree AAU

  22. Questions? AAU

  23. Thank You ! Presented by YuQing Zhang

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