Network Performance Testing System Integrating Models for Automatic QoE Evaluation of Popular Services: YouTube and Facebook

详细信息    查看全文

• 作者：Francisco Lozano ; Gerardo Gómez…
• 关键词：Quality of experience ; Mean opinion score ; $$\hbox {YouTube}^{\mathrm{TM}}$$ YouTube TM ; Facebook ; Android
• 刊名：Wireless Personal Communications
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：81
• 期：4
• 页码：1377-1397
• 全文大小：2,261 KB
• 参考文献：1. Cisco Systems Inc.,(2013). Cisco visual networking index: Forecast and methodology, 2013-018. http://www.cisco.com. Accessed Oct 2014.
  2. YouTube Press Room. (2014). Statistics. https://www.youtube.com/yt/press/statistics.html. Accessed Oct 2014.
  3. Experian Hitwise US. (2014). Social media trends. http://www.experian.com/hitwise/online-trends-social-media.html. Accessed Oct 2014.
  4. ITU-T, Recommendation. (1996). P.800. Methods for subjective determination of transmission quality. Available at http://www.itu.int/rec/T-REC-P.800-199608-I/en
  5. Begen, A, Akgul, T, Baugher, M (2011) Watching video over the web: Part 1: Streaming protocols. IEEE Internet Computing 15: pp. 54 CrossRef
  6. Ameigeiras, P, Ramos-Munoz, JJ, Navarro-Ortiz, J, Lopez-Soler, J (2012) Analysis and modelling of youtube traffic. Transactions on Emerging Telecommunications Technologies 23: pp. 360 CrossRef
  7. Gonzlez, R, Wintz, P (1987) Digital image processing. Addison-Wesley Publishing Co., London
  8. Wang, Z., Lu, L., & Bovik, A. (2002). Video quality assessment using structural distortion measurement. In / Proceedings on the 2002 International Conference on Image Processing, vol. 3, pp. 65-8.
  9. ITU-T, Recommendation. (2008). J.247. Objective perceptual multimedia video quality measurement in the presence of a full reference. Available at http://www.itu.int/rec/T-REC-J.247-200808-I/en
  10. ITU-T, Recommendation. (2004). J.144. Objective perceptual video quality measurement techniques for digital cable television in the presence of a full reference. Available at http://www.itu.int/rec/T-REC-J.144-200403-I/en
  11. Mok, R., Chan, E., & Chang, R. (2011). Measuring the quality of experience of http video streaming. In / Integrated Network Management (IM), 2011 IFIP/IEEE International Symposium on, pp. 485-92.
  12. Gómez, G., Hortigüela, L., Pérez, Q., Lorca, J., García, R., & Aguayo-Torres, M.C. (2014). Youtube qoe evaluation tool for android wireless terminals. / EURASIP Journal on Wireless Communications and Networking 2014, / 2014, 164.
  13. Facebook Inc., (2014). Facebook developers. https://developers.facebook.com/. Accessed Oct 2014.
  14. Jung, I., Kim, H., Hong, D.K., & Ju, H. (2013). Protocol reverse engineering to facebook messages. In / 2013 4th International conference on intelligent systems modelling simulation (ISMS), pp. 539-42.
  15. Casas, P., Sackl, A., Egger, S., & Schatz, R. (2012). Youtube and facebook quality of experience in mobile broadband networks. In / IEEE Globecom Workshops, pp. 1269-274.
  16. Ameigeiras, P, Ramos-Munoz, JJ, Navarro-Ortiz, J, Mogensen, P, Lopez-Soler, JM (2010) QoE oriented cross-layer design of a resource allocation algorithm in beyond 3G systems. Computer Communications 33: pp. 571 CrossRef
  
• 刊物类别：Engineering
• 刊物主题：Electronic and Computer Engineering
  Signal,Image and Speech Processing
  Processor Architectures
  
• 出版者：Springer Netherlands
• ISSN：1572-834X

文摘

Smartphones have significantly changed the traffic pattern usage of mobile subscribers. In addition to the classical file sharing and web browsing usage, social networking applications and access to video content are now a significant percentage of the typical user data traffic consumption. As the change in usage pattern affects the performance of mobile networks, operators need methods to estimate how well the network behaves. The metrics to use for the evaluation of the quality of experience (QoE) are only well documented for traditional applications. In this paper a novel QoE system that automatically captures and processes the metrics needed to evaluate two commonly used applications, the social networking application Facebook and the video download application YouTube, is presented. The system uses a test application developed for Android phones, which report the results to a centralized platform capable of processing and presenting the results in different formats. The system has been used to test those two services over 3G/LTE network technologies. In the case of the YouTube services, performance results show a subjective score very similar for the 3G and LTE because of the automatic adaptation of the video coding rate to the network conditions. Testing of the Facebook application has led to the proposal of a new MOS expression that takes into account the content type being posted, which provides more reasonable MOS estimations than the generic web browsing models available in the literature and commonly used to estimate Facebook QoE.