A Novel Method for Predictive Aggregate Queries over Data Streams in Road Networks Based on STES Methods

  • Jun Feng
  • Yaqing Shi
  • Zhixian Tang
  • Caihua Rui
  • Xurong Min
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8482)


Effective real-time traffic flow prediction can improve the status of traffic congestion. A lot of traffic flow predictive methods focus on vehicles’ specific information (such as vehicles id, position, speed, etc.). This paper proposes a novel method for predictive aggregate queries over data streams in road networks based on STES methods. The novel method obtains approximate aggregate queries results by less storage space and time consuming. Experiments show that it can better do aggregate prediction compared with the ES methods based on DynSketch, as well as SAES method based on DS.


road networks data streams STES methods predictive aggregate queries 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jun Feng
    • 1
  • Yaqing Shi
    • 1
    • 2
  • Zhixian Tang
    • 1
  • Caihua Rui
    • 1
  • Xurong Min
    • 3
  1. 1.College of Computer and InformationHohai UniversityNanjingChina
  2. 2.Command Information System InstitutePLA University of Science and TechnologyNanjingChina
  3. 3.Computer Information Management Center of Nanjing Labor and Social Security BureauNanjingChina

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