Advertisement

Mobile Networks and Applications

, Volume 23, Issue 4, pp 1082–1088 | Cite as

Fine-Grained Big Traffic Data Reverse-charge System: A Method of Saving Expenses

  • Xin Su
  • Leilei Meng
  • Ziyu Wang
  • Chunsai Du
  • Chang Choi
Article
  • 68 Downloads

Abstract

The number of mobile users and the volume of big traffic data generated by user terminals are dramatically increased with diverse applications. Development in different economic and social sectors not only require higher network speed but also need low-cost on information exchanges. The market needs a complete set of solutions, which can provide a comprehensive management system for the operation and billing of a fine-grained data traffic system. This study addresses issues related to big traffic data reverse-charge for customers, which is a new type of consumption model that enables customers to save money with the cooperation of operators and online enterprises. We apply virtual private networking to identify apps, so as to help operators easily calculate the big traffic data of each app and reverse the related charges from the consumer to the relevant online enterprise. Online enterprises are willing to pay the expenses of some of their apps to enhance the user experience of customers exploring wireless services. To prove the popularity of our proposed system, we have experimentally employed the proposed reverse charge system, and participants’ responses to questionnaires indicate a win−win situation for customers as well as online enterprises. We hope that the proposed system will be implemented in practice, subject to customers, online enterprises, and operators agreeing to upgrade conventional charging infrastructures.

Keywords

VPN Big traffic data Android IOS 

Notes

Acknowledgments

This research was funded by the Natural Science Foundation of Jiangsu Province under Grant BK20160287. This research was also funded by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education (No. 2017R1A6A1A03015496) and by the National Research Foundation of Korea (NRF) grant funded by the Korea government(Ministry of Science and ICT) (No. 2017R1E1A1A01077913).

Compliance with Ethical Standards

Conflict of interests

The authors declare that they have no conflict of interest.

References

  1. 1.
    Wan H, Lin Y, Wu Z, Huang H (2012) Discovering typed communities in mobile social networks. Journal of Computer Science and Technology.  https://doi.org/10.1007/s11390-012-1237-9
  2. 2.
    Hou J, Baowen X, Lei X, Wang D, Xu J (2008) A testing method for Web services composition based on data-flow. Wuhan University Journal of Natural Sciences.  https://doi.org/10.1007/s11859-008-0415-8
  3. 3.
    Tihua Y, Baoshu W (2006) Grid architecture model of network centric warfare. Journal of Systems Engineering and Electronics.  https://doi.org/10.1016/S1004-4132(06)60022-4
  4. 4.
    Rodić A, Jovanović M, Stevanović I, Karan B, Potkonjak V (2015) Building technology platform aimed to develop service robot with embedded personality and enhanced communication with social environment. Digital Communications and Networks.  https://doi.org/10.1016/j.dcan.2015.03.002
  5. 5.
    Yang L, Ren Y, Zhang W (2016) 3D depth image analysis for indoor fall detection of elderly people. Digital Communications and Networks.  https://doi.org/10.1016/j.dcan.2015.12.001
  6. 6.
    Alshalan A, Pisharody S, Huang D (2016) A survey of mobile VPN technologies. IEEE Communications Surveys & Tutorials.  https://doi.org/10.1109/COMST.2015.2496624
  7. 7.
    Harikumar AK, Lee R, Yang HS, Kim H-K, Kang B (2005) A model for application integration using web services. In: Proceedings of annual ACIS international conference on computer and information science.  https://doi.org/10.1109/ICIS.2005.12
  8. 8.
    Paris DL, Bahari M, Iahad NA (2016) Business-to-customer (B2C) electronic commerce: an implementation process view. In: Proceedings of 2016 3rd international conference on computer and information sciences (ICCOINS).  https://doi.org/10.1109/ICCOINS.2016.7783182
  9. 9.
    Berger T (2006) Analysis of current VPN technologies. In: Proceedings of the 1st international conference on availability, reliability and security (ARES’06).  https://doi.org/10.1109/ARES.2006.30
  10. 10.
    Jain RK, Trivedi P (2006) OSSEC based authentication process with minimum encryption and decryption time for virtual private network. In: Proceedings of 8th international conference on computational intelligence and communication networks.  https://doi.org/10.1109/CICN.2016.92
  11. 11.
    Saad T, Alawieh B, Mouftah HT, Gulder S (2006) Tunneling techniques for end-to-end VPNs: generic deployment in an optical testbed environment. IEEE Communications Magazine .  https://doi.org/10.1109/MCOM.2006.1637957
  12. 12.
    Li M (2001) Policy-based IPsec management. IEEE Communications Magazine.  https://doi.org/10.1109/MNET.2003.1248659
  13. 13.
    Chou W (2002) Inside SSL: the secure sockets layer protocol. IT Professional.  https://doi.org/10.1109/MITP.2002.1046644
  14. 14.
    Ahmed M (2017) Thwarting DoS attacks: a framework for detection based on collective anomalies and clustering. Computer.  https://doi.org/10.1109/MC.2017.3571051
  15. 15.
    Zhou J (1999) Fixing of security flaw in IKE protocols. Electronics Letters.  https://doi.org/10.1049/el:19990747
  16. 16.
    Good T, Benaissa M (2009) 692-nW Advanced Encryption Standard (AES) on a 0.13-mum CMOS. IEEE Transactions on Very Large Scale Integration (VLSI) Systems.  https://doi.org/10.1109/TVLSI.2009.2025952
  17. 17.
    Ren Y, Wu L, Li H, Li X, Zhang X, Wang A, Chen H (2016) Key recovery against 3DES in CPU smart card based on improved correlation power analysis. Tsinghua Science and Technology.  https://doi.org/10.1109/TST.2016.7442503
  18. 18.
    Bayat-Sarmadi S, Mozaffari-Kermani M, Reyhani-Masoleh A (2014) Efficient and concurrent reliable realization of the secure cryptographic SHA-3 algorithm. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.  https://doi.org/10.1109/TCAD.2014.2307002
  19. 19.
    Ou Y-L, Zhang L-N, Nan Y (2010) Researching on MD5’s characteristics based on software reversing. The Journal of China Universities of Posts and Telecommunications.  https://doi.org/10.1016/S1005-8885(09)60593-8
  20. 20.
    J.D’Orazio C, Choo K-KR (2017) A technique to circumvent SSL/TLS validations on IOS devices. Future Generation Computer Systems.  https://doi.org/10.1016/j.future.2016.08.019

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Xin Su
    • 1
  • Leilei Meng
    • 1
  • Ziyu Wang
    • 2
  • Chunsai Du
    • 3
  • Chang Choi
    • 4
    • 5
  1. 1.College of IOT Engineering, Changzhou Key Laboratory of Robotics and Intelligent TechnologyHohai UniversityChangzhouChina
  2. 2.Ivtime Information Technology Co., Ltd.NanjingChina
  3. 3.College of Automation, Nanjing Key Laboratory of Automatic Measurement TechnologySoutheast UniversityNanjingChina
  4. 4.Department of Computer EngineeringChosun UniversityGwangjuSouth Korea
  5. 5.IT Research InstituteChosun UniversityGwangjuSouth Korea

Personalised recommendations