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

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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.

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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).

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Authors and Affiliations

  1. College of IOT Engineering, Changzhou Key Laboratory of Robotics and Intelligent Technology, Hohai University, Changzhou, 213022, China

    Xin Su & Leilei Meng

  2. Ivtime Information Technology Co., Ltd., Nanjing, 210000, China

    Ziyu Wang

  3. College of Automation, Nanjing Key Laboratory of Automatic Measurement Technology, Southeast University, Nanjing, 210096, China

    Chunsai Du

  4. Department of Computer Engineering, Chosun University, Gwangju, 61452, South Korea

    Chang Choi

  5. IT Research Institute, Chosun University, Gwangju, 61452, South Korea

    Chang Choi

Authors
  1. Xin Su
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  2. Leilei Meng
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  3. Ziyu Wang
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  4. Chunsai Du
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  5. Chang Choi
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Correspondence to Chang Choi.

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Su, X., Meng, L., Wang, Z. et al. Fine-Grained Big Traffic Data Reverse-charge System: A Method of Saving Expenses. Mobile Netw Appl 23, 1082–1088 (2018). https://doi.org/10.1007/s11036-018-1072-5

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