• DocumentCode
    1388407
  • Title

    ROAD: A New Spatial Object Search Framework for Road Networks

  • Author

    Lee, Ken C K ; Lee, Wang-Chien ; Zheng, Baihua ; Tian, Yuan

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Univ. of Massachusetts Dartmouth, North Dartmouth, MA, USA
  • Volume
    24
  • Issue
    3
  • fYear
    2012
  • fDate
    3/1/2012 12:00:00 AM
  • Firstpage
    547
  • Lastpage
    560
  • Abstract
    In this paper, we present a new system framework called ROAD for spatial object search on road networks. ROAD is extensible to diverse object types and efficient for processing various location-dependent spatial queries (LDSQs), as it maintains objects separately from a given network and adopts an effective search space pruning technique. Based on our analysis on the two essential operations for LDSQ processing, namely, network traversal and object lookup, ROAD organizes a large road network as a hierarchy of interconnected regional subnetworks (called Rnets). Each Rnet is augmented with 1) shortcuts and 2) object abstracts to accelerate network traversals and provide quick object lookups, respectively. To manage those shortcuts and object abstracts, two cooperating indices, namely, Route Overlay and Association Directory are devised. In detail, we present 1) the Rnet hierarchy and several properties useful in constructing and maintaining the Rnet hierarchy, 2) the design and implementation of the ROAD framework, and 3) a suite of efficient search algorithms for single-source LDSQs and multisource LDSQs. We conduct a theoretical performance analysis and carry out a comprehensive empirical study to evaluate ROAD. The analysis and experiment results show the superiority of ROAD over the state-of-the-art approaches.
  • Keywords
    network theory (graphs); roads; search problems; transportation; ROAD; Rnet hierarchy; association directory; interconnected regional subnetworks; location-dependent spatial queries; network traversal; road networks; route overlay; search space pruning technique; single-source LDSQ; spatial object search framework; Artificial neural networks; Indexes; Search problems; Spatial databases; Location-dependent spatial query; and search algorithms.; indexing techniques; spatial road network;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2010.243
  • Filename
    5645632