Efficient Indexing of the Past, Present and Future Positions of Moving Objects on Road Network

  • Ying Fang
  • Jiaheng Cao
  • Yuwei Peng
  • Nengcheng Chen
  • Lin Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7901)


Aim at moving objects on road network, we propose a novel indexing named PPFN*-tree to store past trajectories, present positions, and predict near future positions of moving objects. PPFN*-tree is a hybrid indexing structure which consists of a 2D R*-tree managing the road networks, a set of TB*-tree indexing objects’ movement history trajectory along the polylines, and a set of basic HTPR*-tree indexing the position of moving objects after recent update. PPFN*-tree can not only support past trajectory query and present position query, but also support future predictive query. According to the range query time, query in PPFN*-tree can be implemented only in the TB*-tree, or only in the HTPR*-tree, or both of them. Experimental results show that the update performance of the PPFN*-tree is better than that of the PPFI and the RPPF-tree. The query performance of the PPFN*-tree is better than that of the MON-Tree and the PPFI.


moving object indexing PPFN*-tree TB*-tree HTPR*-tree range query trajectory query 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ying Fang
    • 1
  • Jiaheng Cao
    • 1
  • Yuwei Peng
    • 1
  • Nengcheng Chen
    • 2
  • Lin Liu
    • 2
  1. 1.School of ComputerWuhan UniversityChina
  2. 2.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote SensingWuhan UniversityChina

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