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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Next Generation Networks and Services (NGNS), 2012
         
        
            Conference_Location : 
Faro
         
        
            Print_ISBN : 
978-1-4799-2168-3
         
        
        
            DOI : 
10.1109/NGNS.2012.6656095