• DocumentCode
    2205126
  • Title

    RTIC-C: A Cloud Computing Platform for History Data Mining of Traffic Information

  • Author

    Tongyu Zhu ; Jianjun Yu ; Bowen Du

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    12-16 Dec. 2012
  • Firstpage
    282
  • Lastpage
    283
  • Abstract
    Realtime traffic information system produces massive traffic data with the process of collecting the realtime original transportation data, processing the GPS (Global Positioning System) data and publishing the realtime traffic information, which would bring several issues when we reuse these massive traffic data for history data mining, such as massive storage, high performance processing, open interface. Cloud computing delivers computing and storage capacity as a transparent service, which inspires us to develop a cloud infrastructure for history data mining applications of traffic information named RTIC-C. RTIC-C designs a distributed data management service to support large scale of data storage, a parallel distributed computing framework for diverse kinds of mining applications based on the map-reduce mechanism, finally RTIC-C provides a restful Web services interface to support third-party applications.
  • Keywords
    Global Positioning System; Web services; cloud computing; data mining; parallel processing; traffic information systems; user interfaces; GPS data; RTIC-C; cloud computing platform; distributed data management service; global positioning system; high performance processing; history data mining; open interface; parallel distributed computing framework; realtime original transportation data; restful Web services interface; third-party applications; traffic information system; cloud computing; data mining; real time traffic information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Connected Vehicles and Expo (ICCVE), 2012 International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-4705-1
  • Type

    conf

  • DOI
    10.1109/ICCVE.2012.61
  • Filename
    6519586