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
Link To Document :
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