MOBILITY PREDICTION METHOD FOR VEHICULAR NETWORK USING MARKOV CHAIN
DOI:
https://doi.org/10.11113/jt.v78.8885Keywords:
Markov Chain, mobility prediction, real data traces, vehicular networkAbstract
This paper proposes mobility prediction technique via Markov Chains with an input of user’s mobile data traces to predict the user’s movement in wireless network. The main advantage of this method is prediction will give knowledge of user’s movement in advance even in fast moving vehicle. Furthermore, the information from prediction result will be use to assist handover procedure by reserve resource allocation in advance in vehicular network. This algorithm is simple and can be computed within short time; thus the implementation of this technique will give the significant impact especially on higher speed vehicle. Finally, an experiment is performed using real mobile user data traces as input for Markov chain to predict next user movement. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out with several users under same location zone. The results show that the proposed method predicts have good performance which is 30% of mobile users achieved 100% of prediction accuracy.
References
Nielsen. 2014. Rising Middle Class Will Drive Global Automotive Demand in the Coming Two Years.
Araniti G., Campolo C., Condoluci M., Iera A., and Molinaro A. 2013. LTE for Vehicular Networking : A Survey. IEEE Communications Magazine. 148–157.
Wang C.-X., Haider F., Gao X., You X.-H., Yang Y., Yuan D., Aggoune H. M., Haas H., Fletcher S., and Hepsaydir E. 2014. Cellular Architecture and Key Technologies for 5G Wireless Communication Networks. IEEE Communications Magazine. 122–130.
Ericsson. 2013. 5G Radio Access - Research and Vision.
Kaloxylos A., Barmpounakis S., Spapis P., and Alonistioti N. 2014. An Efficient RAT Selection Mechanism for 5G Cellular Networks. In IWCMC.
Wang Y., Li J., Huang L., Jing Y. 2014. A. Georgakopoulos, and P. Demestichas,5G Mobile. IEEE Vehicular Technology Magazine, September. 39–46.
Zhou Y. and Ai B. 2014. Handover Schemes and Algorithms of High-Speed Mobile Environment: A Survey. Comput. Commun.
Jungnickel V., Manolakis K., Zirwas W., Panzner B., Braun V., Lossow M., Sternad M., Apelfröjd R., and Svensson T. 2014. The Role Of Small Cells, Coordinated Multi-Point And Massive MIMO In 5G. IEEE Communications Magazine.
Hussein Y. S., Ali B. M., Varahram P., and Sali A. 2011. Enhanced Handover Mechanism in Long Term Evolution (LTE) Networks. Sci. Res. Essays. 6(24): 5138–5152.
Deshpande P., Kashyap A., Sung C., and Das S. R., 2009. Predictive Methods for Improved Vehicular Wifi Access. In Proceedings of the 7th international conference on Mobile systems, applications, and services. 263.
Amirrudin N. A. 2013. Mobility Prediction via Markov Model in LTE Femtocell. Int. J. Comput. Appl., 65(18): 40–44.
Zhu K., Niyato D., Wang P., Hossain E., and Kim D. I. 2011. Mobility and Handoff Management in Vehicular Networks : A Survey. Wirel. Commun. Mob. Comput. 459–476.
G. Xue, Y. Luo, J. Yu, and Li M. 2012. A Novel Vehicular Location Prediction Based On Mobility Patterns for Routing In Urban VANET, EURASIP J. Wirel. Commun. Netw. (1): 222.
Feng H., Liu C., Shu Y., and Yang O. W. W. 2014. Location Prediction of Vehicles in VANETs Using A Kalman Filter. Wirel. Pers. Commun.
Lin Y.-B., Huang-Fu C.-C., and Alrajeh N. 2013. Predicting Human Movement Based on Telecom’s Handoff in Mobile Networks. IEEE Trans. Mob. Comput. 12(6): 1236–1241.
Daoui M., M’zoughi a., Lalam M., Belkadi M., and Aoudjit R. 2008. Mobility prediction based on an ant system. Comput. Commun. 31(14): 3090–3097.
Ulvan A., Ulvan M., and Bestak R. 2009. The Enhancement of Handover Strategy by Mobility Prediction in Broadband Wireless Access. in Proceedings of the Networking and Electronic Commerce Research Conference(NAEC 2009). 1–22.
Chen S., Li Y., Ren W., Jin D., and Hui P. 2013. Location Prediction for Large Scale Urban Vehicular Mobility. in Wireless Communications and Mobile Computing Conference (IWCMC). 1733–1737.
Gambs S., Killijian M.-O., and del Prado Cortez M. N. 2012. Next place prediction using mobility Markov chains. Proc. First Work. Meas. Privacy, Mobil. - MPM ’12. 1–6.
Barth D., Bellahsene S., and Kloul L. 2011. Mobility Prediction Using Mobile User Profiles. in 2011 IEEE 19th Annual International Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems. 286–294.
Amirrudin N. A., Ariffin S. H. S., Malik N. N. N. A., and Ghazali N. E. 2013. User’s Mobility History-based Mobility Prediction in LTE Femtocells Network. in IEEE International RF and Microwave Conference (RFM2013). 105–110.
D. Lee, Y. Kim, and H. Lee. 2014. Route Prediction Based Vehicular Mobility Management Scheme for VANET, Int. J. Distrib. Sens. Networks.
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