Skip to main content
Springer Nature Link
Log in

Pricing and Revenue Sharing Between ISPs Under Content Sponsoring

  • Published:
Mobile Networks and Applications Aims and scope Submit manuscript

Abstract

As sponsored data with subsidized access cost gains popularity in industry, it is essential to understand its impact on the Internet service market. We investigate the interplay among Internet Service Providers (ISPs), Content Provider (CP) and End User (EU), where each player is selfish and wants to maximize its own profit. In particular, we consider multi-ISP scenarios, in which the network connectivity between the CP and the EU is jointly provided by multiple ISPs. We first model non-cooperative interaction between the players as a four-stage Stackelberg game, and derive the optimal behaviors of each player in equilibrium. Taking into account the transit price at intermediate ISP, we provide in-depth understanding on the sponsoring strategies of CP. We then study the effect of cooperation between the ISPs to the pricing structure and the traffic demand, and analyze their implications to the players. We further build our revenue sharing model based on Shapley value mechanism, and show that the collaboration of the ISPs can improve their total payoff with a higher social welfare.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. In general, the traffic delivery cost is unlikely to be a linear function of the traffic amount. However, in this work, we focus on the traffic change from the CP of our interest, assuming that it does not substantially change the total traffic amount in the network. In this case, the marginal delivery cost of the traffic can be approximated as a linear function with a marginal cost parameter.

References

  1. Sen S, Joe-Wong C, Ha S, Chiang M (2013) A survey of smart data pricing: Past proposals, current plans, and future trends. ACM Comput Surv 46(2):15

    Article  Google Scholar 

  2. Developing Telecoms (2014) Data monetisation strategies will help telcos capture emerging markets. https://www.developingtelecoms.com/tech/customer-management/7297-data-monetisation-strategies-will-help-telcos-capture-emerging-markets.html. Accessed 30 January 2018

  3. Lotfi MH, Sundaresan K, Sarkar S, Khojastepour MA (2017) Economics of quality sponsored data in Non-Neutral networks. IEEE/ACM Trans Networking 25(4):2068–2081

    Article  Google Scholar 

  4. Zhang L, Wu W, Wang D (2015) Sponsored data plan: a two-class service model in wireless data networks. ACM SIGMETRICS Performance Evaluation Rev 43(1):85–96

    Article  Google Scholar 

  5. Hande P, Chiang M, Calderbank R, Rangan S (2009) Network pricing and rate allocation with content provider participation. IEEE INFOCOM, 990–998

  6. Ma RTB (2016) Subsidization competition: Vitalizing the neutral internet. IEEE/ACM Trans Networking 24 (4):2563–2576

    Article  Google Scholar 

  7. Jin Y, Reiman MI, Andrews M (2015) Pricing sponsored content in wireless networks with multiple content providers. IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 1–6

  8. Andrews M, Ozen U, Reiman MI, Wang Q (2013) Economic models of sponsored content in wireless networks with uncertain demand. Computer Communications Workshops (INFOCOM WKSHPS), 345–350

  9. Wu Y, Kim H, Hande PH, Chiang M, Tsang DHK (2011) Revenue sharing among ISPs in two-sided markets. Proceedings IEEE INFOCOM, 596–600

  10. Brake D (2016) Mobile zero rating: The economics and innovation behind free data. Net Neutrality Reloaded: Zero Rating, Specialised Service. Ad Blocking and Traffic Management, 132

  11. Joe-Wong C, Ha S, Chiang M (2015) Sponsoring mobile data: an economic analysis of the impact on users and content providers. IEEE Conference on Computer Communications (INFOCOM), 1499–1507

  12. Xiong Z, Feng S, Niyato D, Wang P, Zhang Y (2017) Economic analysis of network effects on sponsored content: a hierarchical game theoretic approach. GLOBECOM 2017, 1–6

  13. Quartz Media (2017) The inside story of how Netflix came to pay Comcast for internet traffic. https://qz.com/256586/the-inside-story-of-how-netflix-came-to-pay-comcast-for-internet-traffic/. Accessed 15 January 2018.

  14. Fudenberg D, Tirole J (1993) Game Theory. MIT Press

  15. Kang S, Joo C, Lee J, Shroff N (2018) Pricing for past channel state information in Multi-Channel cognitive radio networks. IEEE Trans Mob Comput 17(4):859–870

    Article  Google Scholar 

  16. Osborne MJ, Rubenstein A (1994) A Course in Game Theory. MIT Press

  17. Joo C, Choi JP (2015) Dynamic Cross-Layer transmission control for Station-Assisted satellite networks. IEEE Trans Aerosp Electron Syst 51(3):1737–1746

    Article  Google Scholar 

  18. Im H, Joo C, Lee T, Bahk S (2016) Receiver-Side TCP Countermeasure to bufferbloat in wireless access networks. IEEE Trans Mob Comput 15(8):2080–2093

    Article  Google Scholar 

  19. Roh HT, Lee JW (2016) Chanel assignment, link scheduling, routing, and rate control for multi-channel wireless mesh networks with directional antennas. J Commun Net 18(6): 884–891

    Article  Google Scholar 

  20. Lee J, Lee K, Jeong E, Jo J, Shroff N (2017) CAS: Context-Aware Background Application Scheduling in Interactive Mobile Systems. IEEE J Selected Areas in Commun 35(2):1013–1029

    Article  Google Scholar 

  21. Brodkin J (2015) Verizon and Cogent settle differences, agree to boost Internet quality. https://arstechnica.com/information-technology/2015/05/verizon-and-cogent-settle-differences-agree-to-boost-internet-quality/. Accessed 17 August 2018

  22. Cogent Communications (2015) Cogent and verizon enter into interconnection agreement. https://www.cogentco.com/en/news/press-releases/714-cogent-and-verizon-enter-into-interconnection-agreement. Accessed 17 August 2018

  23. Shapley L (1953) A Value for n-person Games. In: Kuhn HW, Tucker AW (eds) Contribution to the theory of games of annals of mathematics studies, vol 28. Princeton University Press, Princeton, pp 307–317

  24. Lee H, Jang H, Cho JW, Yi Y (2012) On the stability of ISPs’ coalition structure: Shapley Value based revenue sharing

  25. Lee H, Jang H, Cho JW, Yi Y (2017) Traffic scheduling and revenue distribution among providers in the internet: Tradeoffs and impacts. IEEE J Selected Areas Commun 35(2):421–431

    Article  Google Scholar 

  26. Ma RTB, Chiu DM, Lui JCS, Misra V, Rubenstein D (2011) On cooperative settlement between content, transit, and eyeball internet service providers. IEEE/ACM Trans Networking 19(3):802–815

    Article  Google Scholar 

  27. Ma RTB, Chiu DM, Lui JCS, Misra V, Rubenstein D (2010) Internet economics: The use of shapley value for ISP settlement. IEEE/ACM Trans Networking 18(3):775–787

    Article  Google Scholar 

  28. Susanto H, Liu B, Kim B, Zhang H, Fu X (2015) Pricing and revenue sharing in secondary market of mobile internet access. In: IEEE 34th International Performance, Computing and Communications Conference (IPCCC), 1–8

  29. Satybaldy A, Joo C (2018) Pricing and revenue sharing between isps under content sponsoring. Tech. report. Available at http://netlab.unist.ac.kr/publications/technical-reports/

  30. Satybaldy A, Joo C (2018) Content Sponsoring with inter-ISP Transit Cost. GAMENETS

Download references

Acknowledgements

This work was supported by the NRF grants funded by the Korea government (MSIT) (No. NRF-2017R1E1A1A03070524 and NRF-2017K1A3A1A19070720). C. Joo is the corresponding author. An earlier version of this work has been presented at GAMENETS’18 [30].

Author information

Authors and Affiliations

  1. Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, South Korea

    Abylay Satybaldy & Changhee Joo

Authors
  1. Abylay Satybaldy
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Changhee Joo
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Changhee Joo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Satybaldy, A., Joo, C. Pricing and Revenue Sharing Between ISPs Under Content Sponsoring. Mobile Netw Appl 26, 501–511 (2021). https://doi.org/10.1007/s11036-018-1126-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11036-018-1126-8

Keywords