• DocumentCode
    262326
  • Title

    Extracting Trends of Traffic Congestion Using a NoSQL Database

  • Author

    Damaiyanti, Titus Irma ; Imawan, Ardi ; Joonho Kwon

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Pusan Nat. Univ., Busan, South Korea
  • fYear
    2014
  • fDate
    3-5 Dec. 2014
  • Firstpage
    209
  • Lastpage
    213
  • Abstract
    Recently, there has been growing interest in monitoring the road traffic data. Most of the work focused on real-time traffic data. In this paper, we propose an Extrac system which extracts trend of traffic congestions from historical traffic data and answers the queries about the trends. In Extrac system, we first convert the historical traffic data into traffic patterns then summarize it by applying MapReduce style algorithms. These traffic patterns are store into a NoSQL database. Our implementation demonstrates the feasibility of Extrac for querying traffic information and generating the result.
  • Keywords
    SQL; query processing; real-time systems; road traffic; traffic engineering computing; Extrac system; MapReduce style algorithms; NoSQL database; historical traffic data; real-time traffic data; road traffic data; traffic congestion; traffic information; Data models; Data visualization; Databases; Heating; Market research; Matrix converters; Roads; NoSQL database; historical traffic data; traffic patterns; trends of traffic congestions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/BDCloud.2014.97
  • Filename
    7034788