ENSC 894 - Communication Networks Final Project
Spring 2020

Performance Analysis of YouTube streaming with WiFi

Group 2
Amandeep Kaur (Aman) (aka148@sfu.ca)

Haotian Ye (Tian) (haotiany@sfu.ca)

Ashiv Rao Dhondea (Hans) (hdhondea@sfu.ca)

Abstract

Video streaming is quickly becoming the most common use case for Internet traffic globally. The dominant real-time entertainment service supplier, YouTube, with 23.4% of the daily traffic in North America [1], employs HTTP adaptive streaming, DASH. This is made possible with the ever-increasing Quality of Service (QoS) and bandwidth capabilities of today’s Internet. Technologies used by hosts for video streaming include Ethernet, WiFi and LTE (Long Term Evolution). The popularity of Ethernet is waning as more and more people make use of mobile devices and laptops which do not possess Ethernet ports. Video streaming over LTE is gaining traction in North America as people opt to do their YouTube or Netflix streaming while commuting to work or traveling. While LTE poses interesting challenges to video streaming, it was not investigated in this report because our version of Riverbed Modeler, the Academic Edition version 17.5, does not allow the use of LTE technology. WiFi is now available on university campuses, schools, coffee shops, shopping malls, restaurants and even on public transit in some countries. It has become ubiquitous and it is therefore a good choice of technology to investigate in this report. We make use of Riverbed Modeler to simulate various scenarios and record useful statistics such as throughput and packet delay to see how WiFi performs for video streaming. The platform chosen is YouTube because it is the dominant entertainment service supplier. We show results of simulations in which the video display resolutions was varied from 720p (720 pixels, progressive scan) to 1080p.

Report

The final report can be found here. It can be compiled from our GitHub repository.

Presentation

The final presentation can be found here.

References

[1] Sandvine, “The global internet phenomena report,” Tech. Rep. MSU-CSE-06-2, Sandvine Incorporated, Fremont, California, U.S.A., October 2018. Published Online.

[2] M. Trevisan, D. Giordano, I. Drago, M. M. Munafò, and M. Mellia, “Five years at the edge: Watching internet from the isp network,” IEEE/ACM Transactions on Networking, pp. 1–14, 2020.

[3] A. Rao, A. Legout, Y.-s. Lim, D. Towsley, C. Barakat, and W. Dabbous, “Network characteristics of video streaming traffic,” in Proceedings of the Seventh Conference on emerging Networking EXperiments and Technologies, pp. 1–12, 2011.

[4] “Delivering Live YouTube Content via DASH.” https://developers.google.com/youtube/v3/live/guides/encoding-with-dash Accessed: 2020-03-31.

[5] “ISO/IEC 23009-1:2014 Information technology — Dynamic adaptive streaming over HTTP (DASH) — Part 1: Media presentation description and segment formats.” https://www.iso.org/standard/65274.html Accessed: 2020-03-31.

[6] “ISO/IEC 23009-1:2019 Information technology — Dynamic adaptive streaming over HTTP — Part 1: Media presentation description and segment formats.” https://www.iso.org/standard/75485.html Accessed: 2020-03-31.

[7] “MPEG ratifies its draft standard for DASH.” https://web.archive.org/web/20120820233136/http://mpeg.chiariglione.org/meetings/geneva11-1/geneva_press.htm Accessed: 2020-03-31.

[8] S. Lederer, C. Müller, and C. Timmerer, “Dynamic adaptive streaming over http dataset,” in Proceedings of the 3rd Multimedia Systems Conference, MMSys ’12, (New York, NY,USA), p. 89–94, Association for Computing Machinery, 2012.

[9] “Adaptive Streaming Overview.” https://commons.wikimedia.org/w/index.php?curid=20054893 Accessed: 2020-03-31.

[10] W. D. D. Maza, “ href="https://hal.archives-ouvertes.fr/hal-01362445/document">A framework for generating http adaptive streaming traffic in ns-3,” in EAI International Conference on Simulation Tools and Techniques, 2016.

[11] S. Banerji and R. S. Chowdhury, “On IEEE 802.11: wireless LAN technology,” International Journal of Mobile Network Communications & Telematics (IJMNCT), vol. 3, 2013.

[12] “Change the Wi-Fi Channel Number to Avoid Interference.” https://www.lifewire.com/wifi-channel-number-change-to-avoid-interference-818208 Accessed: 2020-03-31.

[13] “Quality of Service.” https://www.cs.rutgers.edu/~pxk/417/notes/03-qos.html Accessed: 2020-03-31.

[14] “Riverbed Modeler.” https://cms-api.riverbed.com/portal/community_home Accessed: 2020-03-26.

[15] “nsnam wiki.” https://www.nsnam.org/wiki/Main_Page Accessed: 2020-01-25.

[16] “What are the restrictions for riverbed modeler academic edition 17.5?.” https://supportkb.riverbed.com/support/index?page=content&id=S24443 Accessed: 2020-04-05.

[17] Y. M. Hassan, A. Helmy, and M. M. Rehan, “Effect of varying segment size on dash streaming quality for mobile user,” in 2014 International Conference on Engineering and Technology (ICET), pp. 1–4, April 2014.

[18] M. A. Mohamed and H. F. Ibrahim, “Performance evaluation for video streaming data over lte-a networks,” in 2017 12th International Conference on Computer Engineering and Systems (ICCES), pp. 701–707, Dec 2017.

[19] X. Zhenpeng, “Video Streaming over the 802.11g WLAN Technologies.

[20] S. Calzada, C. Rietchel, and T. Szajner, “Performance Analysis of a Wireless Home Network."

[21] A. Singh and D. Labayo, “Performance Analysis of Video Streaming over Wi-Fi and Ethernet.

[22] J. Kim, J. Zheng, and P. Bertsch, “Video Streaming over Wi-Fi.

[23] M. Ng and C. H. Weng, “Video Streaming over WiFi using Riverbed Modeler.

[24] “802.11n-2009 - IEEE Standard for Information technology– Local and metropolitan area networks– Specific requirements– Part 11: Wireless LAN Medium Access Control (MAC)and Physical Layer (PHY) Specifications Amendment 5: Enhancements for Higher Throughput.” https://standards.ieee.org/standard/802_11n-2009.html Accessed: 2020-04-15.