Research Article
Mobility Patterns Mining Algorithms with Fast Speed
@ARTICLE{10.4108/eai.5-11-2015.150603, author={Giang Minh Duc and Le Manh and Do Hong Tuan}, title={Mobility Patterns Mining Algorithms with Fast Speed}, journal={EAI Endorsed Transactions on Context-aware Systems and Applications}, volume={2}, number={6}, publisher={EAI}, journal_a={CASA}, year={2015}, month={11}, keywords={mobility patterns, mobility rules, cellular communication networks, data mining, mobility prediction.}, doi={10.4108/eai.5-11-2015.150603} }- Giang Minh Duc
Le Manh
Do Hong Tuan
Year: 2015
Mobility Patterns Mining Algorithms with Fast Speed
CASA
EAI
DOI: 10.4108/eai.5-11-2015.150603
Abstract
In recent years, mobile networks and its applications are developing rapidly. Therefore, the issue to ensure quality of service (QoS) is a key issue for the service providers. The movement prediction of Mobile Users (MUs) is an important problem in cellular communication networks. The movement prediction applications of MUs include automatic bandwidth adjustment, smart handover, location based services,… In this work, we propose two new algorithms named the FindUMP1 algorithm and the FindUMP2 algorithm for mining the next movements of the mobile users. In the FindUMP1 algorithm, we make to reduce the complexity of the traditional UMPMining algorithm. In the FindUMP2 algorithm, we perform to reduce the number of transactions of the User Actual Paths (UAPs) database. The results of our experiments show that our proposed algorithms outperform the traditional UMPMining algorithm in terms of the execution time. In addition, we also propose the UMPOnline algorithm in order to reduce the execution time as adding new data. The benefit of applying the UMPOnline algorithm is that the system can run online in real time. Therefore, we can perform the applications effectively.
Copyright © 2015 Giang Minh Duc et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
