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Profile based location update for cellular network using mobile phone data

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Abstract

In the wireless cellular network, location management is one of the intricate dynamic issues that expend the available limited wireless resources in order to guarantee for delivering a call to the mobile device. Towards enhancing the Quality of Service and reducing the dilemma of location management, an improved location update scheme has been proposed in this paper to capture the daily behavioral pattern of the mobile users. Here a profile based LU scheme has been developed according to the mobility pattern of the individual users in a cellular network. Especially, mobile phone data is recorded in a Call Data Record (CDR) data base containing the spatial–temporal information of the millions of anonymized users for consecutive 2 months. In this paper, the proposed profile based LU technique takes into consideration of the individual user movement to optimize the location update characteristics in order to minimize the signaling cost of mobile network. The proposed algorithm shows an improvement of 17% in terms of bandwidth compared to the conventional technique. The use of CDR data for profiling the users, the mathematical formulation which has not yet been used by the other researchers and validation of the algorithm based on actual user data rather than theoretically predicted data are the novelty of this work.

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References

  • Al-Surmi I, Othman M, Mohd Ali B (2012) Mobility management for IP-based next generation mobile networks: review, challenge and perspective. J Netw Comput Appl 35:295–315

    Article  Google Scholar 

  • Barth D, Bellahsene S, Kloul LXE La (2011) Mobility prediction using mobile user profiles. 2011 IEEE 19th Annu. Int. Symp. Model. Anal. Simul. Comput. Telecommun. Syst., pp 286–294

  • Bonchi F, Lakshmanan LVS, Wang(Wendy) H (2011) Trajectory anonymity in publishing personal mobility data. ACM SIGKDD Explor Newsl 13:30

    Article  Google Scholar 

  • Calabrese F, Di Lorenzo G, Liu L, Ratti C (2011) Estimating origin-destination flows using mobile phone location data. IEEE Pervasive Comput 10:36–44. https://doi.org/10.1109/MPRV.2011.41

    Article  Google Scholar 

  • Calabrese F, Diao M, Di Lorenzo G et al (2013) Understanding individual mobility patterns from urban sensing data: a mobile phone trace example. Transp Res Part C Emerg Technol 26:301–313. https://doi.org/10.1016/j.trc.2012.09.009

    Article  Google Scholar 

  • Christin D, Reinhardt A, Kanhere SS, Hollick M (2011) A survey on privacy in mobile participatory sensing applications. J Syst Softw 84:1928–1946. https://doi.org/10.1016/j.jss.2011.06.073

    Article  Google Scholar 

  • Feng L, Zhao Q, Zhang H (2007) Location management based on distance and direction for PCS networks. Comput Networks 51:134–152. https://doi.org/10.1016/j.comnet.2006.04.014

    Article  MATH  Google Scholar 

  • Hsiao M-H, Chen L-C (2015) Smart phone demand: an empirical study on the relationships between phone handset, Internet access and mobile services. Telemat Informatics 32:158–168. https://doi.org/10.1016/j.tele.2014.06.001

    Article  Google Scholar 

  • Hsu WJ, Spyropoulost T, Psounis K, Helmy A (2007) Modeling time-variant user mobility in wireless mobile networks. In: Proceedings—IEEE INFOCOM, pp 758–766

  • Ji Y, Sproul G, Biaz S (2008) NET 14-1—FreeMobility: dynamic localization using GIS. IEEE Wirel Commun Netw Conf 2008:2408–2413. https://doi.org/10.1109/WCNC.2008.424

    Article  Google Scholar 

  • Kondepu K, Kumar C, Tripathi R (2008) Partially overlapping super location area (POSLA): an efficient scheme for location management in PCS networks. Vehicular Technology Conference, pp 2182–2187. https://doi.org/10.1109/VETECS.2008.487

  • Lee L-T, Wu C-F (2007) An HMM-based call admission control policy for supporting QoS in wireless cellular networks. Comput Electr Eng 33:153–165. https://doi.org/10.1016/j.compeleceng.2006.11.002

    Article  MATH  Google Scholar 

  • Li K, Member S (2013) Analysis of distance-based location management in wireless communication networks. IEEE Trans Parallel Distrib Syst 24:225–238

    Article  Google Scholar 

  • Lin Y, Haung Y, Chen Y (2001) Mobility management: from GPRS to UMTS. Wirel Commun Mob Comput 1:339–359. https://doi.org/10.1002/wcm.27

    Article  Google Scholar 

  • Mukherjee A, De D (2016) Location management in mobile network: a survey. ScienceDirect 19:1–14

    MathSciNet  Google Scholar 

  • Pollini GP (1997) A profile-based location strategy and its performance. IEEE J Sel Areas Commun 15:1415–1424

    Article  Google Scholar 

  • Roy A, Misra A, Das SK (2007) Location update versus paging trade-off in cellular networks: an approach based on vector quantization. IEEE Trans Mob Comput 6:1426–1440. https://doi.org/10.1109/TMC.2007.1059

    Article  Google Scholar 

  • Sabatelli A (2018) Method and apparatus for displaying data regarding a device’s traversal through a region. US Patent Appl 10.02505821.2505829

  • Schneider CM, Rudloff C (2013) Daily travel behavior: lessons from a week-long survey for the extraction of human mobility motifs related information. Proc 2nd. https://doi.org/10.1145/2505821.2505829

  • Shen L, Stopher PR (2014) Review of GPS travel survey and GPS data-processing methods. Transp Rev 34:316–334. https://doi.org/10.1080/01441647.2014.903530

    Article  Google Scholar 

  • Sidhu B, Singh H (2007) Location management in cellular networks. Proc world Acad Sci Technol 21:314–319

    Google Scholar 

  • Song C, Qu Z, Blumm N, Barabasi A-L (2010) Limits of predictability in human mobility. Science 80(327):1018–1021. https://doi.org/10.1126/science.1177170

    Article  MathSciNet  MATH  Google Scholar 

  • Tj Gerpott, Thomas S, Weihert M (2018) Correlates of using the billing system of a mobile network operator to pay for dogital goods ansd services, information systems frontiers. Springer, New York

    Google Scholar 

  • Toril M, Luna-Ramírez S, Wille V, Skehill R (2009) Analysis of user mobility statistics for cellular network re-structuring. In: IEEE vehicular technology conference

  • Vukovic M, Lovrek I, Jevtic D (2007) Predicting user movement for advanced location-aware services. 2007 15th Int Conf Software, Telecommun Comput Networks, pp 1–5. https://doi.org/10.1109/softcom.2007.4446120

  • Wang P, Akyildiz IF (2010) Effects of different mobility models on traffic patterns in wireless sensor networks. Proceedings of the Global Communications Conference, 2010. GLOBECOM 2010, 6–10 December 2010, Miami, Florida, USA. https://doi.org/10.1109/GLOCOM.2010.5684190

  • Wang J, Zhang H, Toril M, Wille V (2007) Trial results of intelligent paging in GERAN. IEEE Commun Lett 11:829–831

    Article  Google Scholar 

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Acknowledgements

The authors deeply thank the Director of Bharat Sanchar Nigam Limited (BSNL) for enormous support in access to the data required for the research work.

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Authors and Affiliations

  1. NIT Rourkela, Rourkela, India

    Smita Parija & Prasanna Kumar Sahu

  2. School of Electronics Engineering, Kalinga Institute of Industrial Technology, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Swati Swayamsiddha & Sudhansu Sekhar Singh

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  1. Smita Parija
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  2. Swati Swayamsiddha
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  3. Prasanna Kumar Sahu
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  4. Sudhansu Sekhar Singh
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Correspondence to Smita Parija.

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Parija, S., Swayamsiddha, S., Sahu, P.K. et al. Profile based location update for cellular network using mobile phone data. Microsyst Technol 27, 369–377 (2021). https://doi.org/10.1007/s00542-019-04367-6

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  • DOI: https://doi.org/10.1007/s00542-019-04367-6

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