T-comm Vol. 3. #4-2019 модели обеспечения qoe для ott сервисов



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modeli-obespecheniya-qoe-dlya-ott-servisov

T-Comm Tом 13. #4-2019
14
СВЯЗЬ
MODELS OF QOE ENSURING FOR OTT SERVICES
Vasiliy S. Elagin,
SPbGUT, St. Petersburg, Russia,
elagin.vas@gmail.com
Ilya A. Belozertsev
, SPbGUT, St. Petersburg, Russia,
ilya.belozercev@outlook.com
Anastasia V. Onufrienko
, SPbGUT, St. Petersburg, Russia,
anastasia.4991@mail.ru
Abstract
The 4G network is becoming commercially large-scale worldwide, and the industry has begun research on fifth-generation (5G) mobile
technologies. All this will increase the variety of multimedia services, especially for over-the-Top (OTT) services. OTT services have
already gained great popularity and contributed to a large consumption of traffic, which offers a load on operators. Management solu-
tion QoE for traditional multimedia services obsolete, which creates new problems in the aspects of the management of yo for suppli-
ers of services. This article discusses the main models that contribute to improving the quality of OTT services. The main parameter
for quality assessment was chosen QoE-Quality of Experience. An analysis was made of a number of factors that directly affect the
assessment of QoE. The second part of the article deals with models that can provide the necessary level of quality for OTT services.
These models were divided into three groups: traffic-based models, application-based models, and speed-based models. The main task
of the study is to find optimal solutions to ensure the quality of OTT services.
Keywords: 
OTT Services, QoE, QoS, MOS, quality models.
References
1. Goldshtein B., EvaginV., Belozertsev I. (2018). About quality of OTT Services in LTE. 
Vestnik Sviazy
. 07, 7, рр. 9-12. (
in Russian
)
2. Elagin V.S., Goldshtein A.B., Onufrienko A.V., Zarubin A.A., Belozertsev I.A. (2018). Synchronization of delay for OTT services in
LTE. 
2018 Systems of Signal Synchronization, Generating and Processing in Telecommunications
(SYNCHROINFO), Minsk, 2018, pp. 1-4.
3. Elagin V.S., Goldshtein B.S., Onufrienko A.V., Zarubin A.A., Savelieva A.A. (2018). The efficiency of the DPI system for identifying
traffic and providing the quality of OTT services. 
2018 Systems of Signals Generating and Processing in the Field of on Board
Communications
, Moscow, Russia, 2018, pp. 1-5.
4. 3GPP TS 26.247, "Transparent End-to-End Packet Switched Streaming Service (PSS); Progressive Download and Dynamic Adaptive
Streaming Over HTTP (3GP-DASH)".
5. Steven Latr, Nicolas Staelens, Pieter Simoens. (2008). On-line estimation of the QoE of progressive download services in multime-
dia access networks[C]. 
ICOMP 2008
, Las Vegas, Nevada, USA. 2008, рр. 14-17.
6. Ricky K.P. Mok, Edmond W.W. Chan, and Rocky K.C. Chang. (2011). Measuring the Quality of Experience of HTTP Video
Streaming[C]. Integrated Network Management (IM), 
2011 IFIP/IEEE International Symposium
, Dublin. 2011, рр. 485-492.
7. Ricky K.P. Mok, Edmond W.W. Chan, and Rocky K.C. Chang. (2002). Inferring the QoE of HTTP Video Streaming from User-
Viewing. Activities [C]. W-MUS [16] S. Mohamed and G. Rubino, "A Study of Real-time Packet Video Quality Using Random Neural
Networks," IEEE Trans. On Circuits and Systems for Video Tech.,2002, 12(12), рр. 1071-1083.
8. International Telecommunication Union. Geneva. Methods for subjective determination of transmission quality. Report ITU
TP.800,1996.
9. Vaneet Aggarwal, Emir Halepovic, Prometheus: Toward Quality-of-Experience Estimation for Mobile Apps from Passive Network
Measurements, ACM HotMobile'14, Santa Barbara, CA, USA, February 26-27, 2014.
10. Balachandran A., Sekar V., Akella A., Seshan S. et al. (2012). A quest for an Internet video Quality-of-Experience, metric. In ACM
HotNets.
11. Maxim Claeys. (2014). Design and Evaluation of a Self-Learning HTTP Adaptive Video Streaming Client, IEEE communications let-
ters. Vol. 18. No. 4, April 2014.
12. Mohamed S. and Rubino G. (2002). A Study of Real-time Packet Video Quality Using Random Neural Networks, IEEE Trans. On
Circuits and Systems for Video Tech., 2002-12, 12(12), pp. 1071-1083.
13. VQEG, "Final report from the video quality experts group on the validation of objective models of video quality assessment".
14. Johan De Vriendt, Danny De Vleeschauwer. (2013). Model for estimating QoE of Video delivered using HTTP Adaptive
Streaming[C], IFIP/IEEE IM, 2013.
Information about authors:
Vasiliy S. Elagin
, associate Professor of the Department of Infocommunication systems of SPbGUT, St. Petersburg, Russia
Ilya A. Belozertsev,
postgraduate, Department of Infocommunication systems of SPbGUT, St. Petersburg, Russia
Anastasia V. Onufrienko,
postgraduate, Department of Infocommunication systems of SPbGUT, St. Petersburg, Russia

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