• DocumentCode
    2104111
  • Title

    Mobility prediction and location management based on data mining

  • Author

    Daoui, Mehammed ; Belkadi, Malika ; Chamek, Lynda ; Lalam, Massinissa ; Hamrioui, Sofiane ; Berqia, Amine

  • Author_Institution
    Lab. de Eecherche en Inf., Univ. Mouloud Mammeri de Tizi Ouzou, Tizi Ouzou, Algeria
  • fYear
    2012
  • fDate
    2-4 Dec. 2012
  • Firstpage
    137
  • Lastpage
    140
  • Abstract
    This paper presents a mobility prediction and location management technique based on one of the most used Data mining technique which is The association rules. Our solution can be implemented on a third-generation mobile network by exploiting the data available on existing infrastructure (roads, locations of base stations, ... etc.) and the users´ displacements history. Simulations carried out using a realistic model of movements showed that our strategy can accurately predict up to 90% of the users´ movements by knowing only their last two movements.
  • Keywords
    3G mobile communication; data mining; mobility management (mobile radio); telecommunication computing; association rules; data mining technique; displacements history; location management technique; mobility prediction technique; third-generation mobile network; Next generation networking; Quality of service; Subspace constraints; Data mining; Mobile networks; location management; prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Next Generation Networks and Services (NGNS), 2012
  • Conference_Location
    Faro
  • Print_ISBN
    978-1-4799-2168-3
  • Type

    conf

  • DOI
    10.1109/NGNS.2012.6656095
  • Filename
    6656095