Skip to main content

Minimising the Churn Out of the Service by Using a Fairness Mechanism

  • Conference paper
  • First Online:
Book cover Computer Networks (CN 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1231))

Included in the following conference series:

Abstract

The paper proposes an algorithm of bandwidth distribution, ensuring fairness to end-users in computer networks. The proposed algorithm divides users into satisfied and unsatisfied users. It provides fairness in terms of quality of experience (QoE) for satisfied users and quality of service (QoS) for unsatisfied users. In this paper, we present detailed comparisons relevant to service providers to show the advantages of the proposed algorithm over the popular max-min algorithm. Our algorithm is designed to provide service providers with a mechanism to minimize the number of end-user terminations of service, which is one of the most desired factors for service providers.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. White paper: Cisco visual networking index: forecast and trends, 2017–2022 (2018)

    Google Scholar 

  2. Spiteri, K., Sitaraman, R., Sparacio, D.: From theory to practice: improving bitrate adaptation in the dash reference player. In: Proceedings of the 9th ACM Multimedia Systems Conference, pp. 123–137 (2018). https://doi.org/10.1145/3204949.3204953

  3. Online: Definition of fairness in English by vocabulary dictionaries. https://www.vocabulary.com/dictionary/fairness. Accessed 7 Feb 2020

  4. Online: Definition of fairness in English by Oxford dictionaries. https://en.oxforddictionaries.com/definition/fairnes. Accessed 7 Feb 2020

  5. Online: Definition of fairness in English by Cambridge dictionaries. https://dictionary.cambridge.org/dictionary/english/fairness. Accessed 7 Feb 2020

  6. Basil, A.O., Mu, M., Al-Sherbaz, A.: A software defined network based research on fairness in multimedia. In: Proceedings of the 1st International Workshop on Fairness, Accountability, and Transparency in MultiMedia. FAT/MM 2019, pp. 11–18. ACM (2019) https://doi.org/10.1145/3347447.3356750

  7. Gupta, V., Krishnamurthy, S.V., Faloutsos, M.: Improving the performance of TCP in the presence of interacting UDP flows in ad hoc networks. In: Mitrou, N., Kontovasilis, K., Rouskas, G.N., Iliadis, I., Merakos, L. (eds.) NETWORKING 2004. LNCS, vol. 3042, pp. 64–75. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24693-0_6

    Chapter  Google Scholar 

  8. Domański, A., Domańska, J., Nowak, S., Czachórski, T.: A contribution to the fair scheduling for the TCP and UDP streams. In: Kwiecień, A., Gaj, P., Stera, P. (eds.) CN 2010. CCIS, vol. 79, pp. 207–216. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13861-4_21

    Chapter  Google Scholar 

  9. Mansy, A., Fayed, M., Ammar, M.: Network-layer fairness for adaptive video streams. In: 2015 IFIP Networking Conference (IFIP Networking), pp. 1–9 (2015). https://doi.org/10.1109/IFIPNetworking.2015.7145310

  10. Narayanan, R., Srinivasan, M., Karthikeya, S.A., Murthy, C.S.R.: A novel fairness-driven approach for heterogeneous gateways’ link scheduling in IoT networks. In: 2017 IEEE International Conference on Communications (ICC), pp. 1–7 (2017). https://doi.org/10.1109/ICC.2017.7996818

  11. Malamos, A.G., Malamas, E.N., Varvarigou, T.A., Ahuja, S.R.: On the definition, modelling, and implementation of quality of service (QoS) in distributed multimedia systems. In: Proceedings of IEEE International Symposium on Computers and Communications (Cat. No. PR00250), pp. 397–403 (1999). https://doi.org/10.1109/ISCC.1999.780929

  12. Brunnström, K., Moor, K., Dooms, A., Egger-Lampl, S., et al.: Qualinet White Paper on Definitions of Quality of Experience (2013)

    Google Scholar 

  13. Jain, R., Chiu, D.M., WR, H.: A quantitative measure of fairness and discrimination for resource allocation in shared computer systems. CoRR cs.NI/9809099 (1998)

    Google Scholar 

  14. Chen, Z., Zhang, C.: A new measurement fornetwork sharing fairness. Comput. Math. Appl. 50(5), 803–808 (2005)

    Article  MathSciNet  Google Scholar 

  15. Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27(3), 379–423 (1948). https://doi.org/10.1002/j.1538-7305.1948.tb01338.x

    Article  MathSciNet  MATH  Google Scholar 

  16. Nowicki, K., Malinowski, A., Sikorski, M.: More just measure of fairness for sharing network resources. In: Gaj, P., Kwiecień, A., Stera, P. (eds.) CN 2016. CCIS, vol. 608, pp. 52–58. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39207-3_5

    Chapter  Google Scholar 

  17. Hossfeld, T., Skorin-Kapov, L., Heegaard, P.E., Varela, M.: Definition of QoE fairness in shared systems. IEEE Commun. Lett. 21(1), 184–187 (2017). https://doi.org/10.1109/LCOMM.2016.2616342

    Article  Google Scholar 

  18. Hossfeld, T., Skorin-Kapov, L., Heegaard, P.E., Varela, M.: A new QoE fairness index for QoE management. Qual. User Exp. 3(1), 4 (2018). https://doi.org/10.1007/s41233-018-0017

    Article  Google Scholar 

  19. Martinez-Yelmo, I., Seoane, I., Guerrero, C.: Fair Quality of Experience (QoE) measurements related with networking technologies. In: Osipov, E., Kassler, A., Bohnert, T.M., Masip-Bruin, X. (eds.) WWIC 2010. LNCS, vol. 6074, pp. 228–239. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13315-2_19

    Chapter  Google Scholar 

  20. Shaikh, J., Fiedler, M., Collange, D.: Quality of Experience from user and network perspectives. Ann. Telecommun. Annales des Télécommunications 65(1), 47–57 (2010). https://doi.org/10.1007/s12243-009-0142

    Article  Google Scholar 

  21. Piamrat, K., Viho, C., Bonnin, J., Ksentini, A.: Quality of experience measurements for video streaming over wireless networks. In: 2009 Sixth International Conference on Information Technology: New Generations, pp. 1184–1189 (2009) https://doi.org/10.1109/ITNG.2009.121

  22. Georgopoulos, P., Elkhatib, Y., Broadbent, M., Mu, M., Race, N.: Towards network-wide QoE fairness using openflow-assisted adaptive video streaming. In: Proceedings of the 2013 ACM SIGCOMM Workshop on Future Human-centric Multimedia Networking, pp. 15–20 (2013). https://doi.org/10.1145/2491172.2491181

  23. Brun, J., Safaei, F., Boustead, P.: Fairness and playability in online multiplayer games. In: 3rd IEEE Consumer Communications and Networking Conference, vol. 2, pp. 1199–1203 (2006). https://doi.org/10.1109/CCNC.2006.1593228

  24. Zander, S., Leeder, I., Armitage, G.: Achieving fairness in multiplayer network games through automated latency balancing. In: Proceedings of the 2005 ACM SIGCHI International Conference on Advances in Computer Entertainment Technology, pp. 117–124 (2005). https://doi.org/10.1145/1178477.1178493

  25. Hirota, R., icm Kuribayash, S.: Evaluation of fairness in multiplayer network games. In: Proceedings of 2011 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp. 7–11 (2011)

    Google Scholar 

  26. Deressa, M., Sheng, M., Wimmers, M., Liu, J., Mekonnen, M.: Maximizing quality of experience in device-to-device communication using an evolutionary algorithm based on users’ behavior. IEEE Access 5, 3878–3888 (2017). https://doi.org/10.1109/ACCESS.2017.2685420

    Article  Google Scholar 

  27. Le Boudec, J.Y.: Rate adaptation. A Tutorial, Congestion Control and Fairness (2005)

    Google Scholar 

  28. Kushner, H.J., Whiting, P.A.: Convergence of proportional-fair sharing algorithms under general conditions. IEEE Trans. Wirel. Commun. 3(4), 1250–1259 (2004)

    Article  Google Scholar 

  29. Briscoe, B.: Flow rate fairness: dismantling a religion. SIGCOMM Comput. Commun. Rev. 37(2), 63–74 (2007)

    Article  Google Scholar 

  30. Mueller, C., Lederer, S., Timmerer, C.: An evaluation of dynamic adaptive streaming over HTTP in vehicular environments. In: Proceedings of the 4th Workshop on Mobile Video, pp. 37–42. Association for Computing Machinery (2012). https://doi.org/10.1145/2151677.2151686

  31. Akhshabi, S., Narayanaswamy, S., Begen, A.C., Dovrolis, C.: An experimental evaluation of rate-adaptive video players over HTTP. Image Commun. 27(4), 271–287 (2012)

    Google Scholar 

  32. Akhtar, Z., et al.: Oboe: auto-tuning video ABR algorithms to network conditions. In: Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication, pp. 44–58 (2018). https://doi.org/10.1145/3230543.3230558

  33. Bentaleb, A., Begen, A.C., Zimmermann, R.: SDNDASH: improving QoE of HTTP adaptive streaming using software defined networking. In: Proceedings of the 24th ACM International Conference on Multimedia, pp. 1296–1305 (2016). https://doi.org/10.1145/2964284.2964332

  34. ITU-T: Recommendation P.800 - Methods for subjective determination of transmission quality. International Telecommunication Union (1996)

    Google Scholar 

  35. Hossfeld, T., Heegaard, P.E., Skorin-Kapov, L., Varela, M.: No silver bullet: QoE metrics, QoE fairness, and user diversity in the context of QoE management. In: 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX), pp. 1–6 (2017). https://doi.org/10.1109/QoMEX.2017.7965671

  36. Reichl, P., Egger, S., Schatz, R., D’Alconzo, A.: The logarithmic nature of QoE and the role of the Weber-Fechner law in QoE Assessment. In: 2010 IEEE International Conference on Communications, pp. 1–5 (2010). https://doi.org/10.1109/ICC.2010.5501894

  37. Mazur, I.: Ensuring of fairness in high speed computer networks. M.Sc. thesis, University of Technology Gdansk (2018)

    Google Scholar 

  38. Egger-Lampl, S., Reichl, P., Hossfeld, T., Schatz, R.: Time is bandwidth? Narrowing the gap between subjective time perception and quality of experience. In: Proceedings of IEEE International Conference on Communications. (2012). https://doi.org/10.1109/ICC.2012.6363769

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Izabela Mazur .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mazur, I., Rak, J., Nowicki, K. (2020). Minimising the Churn Out of the Service by Using a Fairness Mechanism. In: Gaj, P., Gumiński, W., Kwiecień, A. (eds) Computer Networks. CN 2020. Communications in Computer and Information Science, vol 1231. Springer, Cham. https://doi.org/10.1007/978-3-030-50719-0_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-50719-0_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50718-3

  • Online ISBN: 978-3-030-50719-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics