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Quality of Experience Estimation for Video Service Delivery Based on SDN Core Network

  • Maria Makolkina
  • Ammar MuthannaEmail author
  • Steve Manariyo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10531)

Abstract

Video traffic plays an increasingly important role in today’s telecommunication networks. Most services are difficult to imagine without video stream transmission, and it is not only IPTV and OTT services, but also the services of augmented reality that are gaining popularity. At the same time, users’ requirements for quality of experience provision are constantly tightened. Therefore, operators need to look for new ways to deliver video content to the user, which will allow the transfer of large amounts of traffic with the appropriate quality of experience. In this article, the possibilities of using SDN networks for the transmission of video traffic are investigated. For this purpose, we have created a laboratory testbed, which consists of a multimedia complex for the delivery of IPTV content and a SDN segment of the network. To estimate the quality of experience of the transmitted video traffic, we used, in addition to the generally accepted parameters, such as delays, losses, throughput, also the Hurst parameter.

Keywords

IPTV Video traffic Soft-Defined Network (SDN) Hurst parameter Quality of experience (QoE) 

Notes

Acknowledgment

The publication was financially supported by the Ministry of Education and Science of the Russian Federation (the Agreement number 02.a03.21.0008), RFBR according to the research project No. 16-37-00209 mol_a “Development of the principles of integration the Real Sense technology and Internet of Things”.

References

  1. 1.
    Bergenti, F., Gotta, D.: Augmented reality for field maintenance of large telecommunication networks. In: Conference and Exhibition of the European Association of Virtual and Augmented Reality (2014)Google Scholar
  2. 2.
    Joo, H.J., Hong, B.H., Lee, E.S., Choi, H.K.: Analysis of IPTV service quality applying real-time QoE measurement technology. In: Park, J., Leung, V., Wang, C.L., Shon, T. (eds.) Future Information Technology, Application, and Service. Lecture Notes in Electrical Engineering, vol. 179, pp. 103–109. Springer, Dordrecht (2012). doi: 10.1007/978-94-007-5064-7_15 CrossRefGoogle Scholar
  3. 3.
    Schatz, R., Hossfeld, T., Casas, P.: Passive youtube QoE monitoring for ISPs. In: 2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), pp. 358–364, July 2012Google Scholar
  4. 4.
    Abdi, L., Abdallah, F.B., Meddev, A.: In-vehicle augmented reality traffic information system: a new type of communication between driver and vehicle. Procedia Comput. Sci. 73, 242–249 (2015)CrossRefGoogle Scholar
  5. 5.
    Zollmann, S., Hoppe, C., Langlotz, T., Reitmayr, G.: FlyAR: augmented reality supported micro aerial vehicle navigation. IEEE Trans. Vis. Comput. Graph. 20, 560–568 (2014)CrossRefGoogle Scholar
  6. 6.
    Makolkina, M., Kirichek, R., Teltevskaya, V., Surodeeva, E.: Research of interaction between applications of augmented reality and control methods of UAVs. In: Koucheryavy, Y., Mamatas, L., Matta, I., Ometov, A., Papadimitriou, P. (eds.) WWIC 2017. LNCS, vol. 10372, pp. 186–193. Springer, Cham (2017). doi: 10.1007/978-3-319-61382-6_15 CrossRefGoogle Scholar
  7. 7.
    Billinghurst, M., Clark, A., Lee, G.: A survey of augmented reality. Found. Trends Hum.-Comput. Interact. 8(2–3), 73–272 (2015)CrossRefGoogle Scholar
  8. 8.
    Putnam, K.: Interconnected wearable devices streamline care delivery. 103(6), P10–P12 (2016). Doi: 10.1016/S0001-2092(16)30220-4
  9. 9.
    Lucrezia, F., Marchetto, G., Risso, F.: In-network support for over-the-top video quality of experience. In: The Sixth International Conference on Advances in Future Internet, AFIN 2014, pp. 72–78 (2014)Google Scholar
  10. 10.
    Makolkina, M., Prokopiev, A., Paramonov, A., Koucheryavy, A.: The quality of experience subjective estimations and the hurst parameters values interdependence. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) NEW2AN 2014. LNCS, vol. 8638, pp. 311–318. Springer, Cham (2014). doi: 10.1007/978-3-319-10353-2_27 Google Scholar
  11. 11.
    Vladyko, A., Muthanna, A., Kirichek, R.: Comprehensive SDN testing based on model network. In: Galinina, O., Balandin, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART -2016. LNCS, vol. 9870, pp. 539–549. Springer, Cham (2016). doi: 10.1007/978-3-319-46301-8_45 CrossRefGoogle Scholar
  12. 12.
    Volkov, A., Khakimov, A., Muthanna, A., Kirichek, R., Vladyko, A., Koucheryavy, A.: Interaction of the IoT traffic generated by a smart city segment with SDN core network. In: Koucheryavy, Y., Mamatas, L., Matta, I., Ometov, A., Papadimitriou, P. (eds.) WWIC 2017. LNCS, vol. 10372, pp. 115–126. Springer, Cham (2017). doi: 10.1007/978-3-319-61382-6_10 CrossRefGoogle Scholar
  13. 13.
    Ushakov, Y., Polezhaev, P., Legashev, L., Bolodurina, I., Shukhman, A., Bakhareva, N.: Increasing the efficiency of IPTV by using software-defined networks. In: Galinina, O., Balandin, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART -2016. LNCS, vol. 9870, pp. 550–560. Springer, Cham (2016). doi: 10.1007/978-3-319-46301-8_46 CrossRefGoogle Scholar
  14. 14.
    Rattanawadee, P., Ruengsakulrach, N., Saivichit, C.: The transmission time analysis of IPTV multicast service in SDN/openflow environments. In: 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), pp. 1–5 (2015)Google Scholar
  15. 15.
    Diallo, M.T., Fieau, F., Abd-Elrahmane, E., Afifi, H.: Utility-based approach for video service delivery optimization. In: International Conference on Systems and Network Communication, ICSNC 2014, pp. 5–10 (2014)Google Scholar
  16. 16.
    Thorpe, C., Olariu, C., Hava, F., McDonagh, P.: Experience of developing an openflow SDN prototype for managing IPTV networks. In: IFIP/IEEE International Symposium on Integrated Network Management (IM), pp. 966–971, May 2015Google Scholar
  17. 17.
    Muhizi, S., Shamshin, G., Muthanna, A., Kirichek, R., Vladyko, A., Koucheryavy, A.: Analysis and performance evaluation of SDN queue model. In: Koucheryavy, Y., Mamatas, L., Matta, I., Ometov, A., Papadimitriou, P. (eds.) WWIC 2017. LNCS, vol. 10372, pp. 26–37. Springer, Cham (2017). doi: 10.1007/978-3-319-61382-6_3 CrossRefGoogle Scholar
  18. 18.
    Makolkina, M., Prokopiev, A., Paramonov, A., Koucheryavy, A.: The quality of experience subjective estimations and the hurst parameters values interdependence. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) NEW2AN 2014. LNCS, vol. 8638, pp. 311–318. Springer, Cham (2014). doi: 10.1007/978-3-319-10353-2_27 Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Maria Makolkina
    • 1
    • 2
  • Ammar Muthanna
    • 1
    Email author
  • Steve Manariyo
    • 1
  1. 1.The Bonch-Bruevich State University of TelecommunicationsSt. PetersburgRussian Federation
  2. 2.Peoples’ Friendship, University of Russia, (RUDN University)MoscowRussian Federation

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