Network characteristics of video streaming traffic

By Ashwin Rao, Arnaud Legout, Yeon-sup Lim, D. Towsley, C. Barakat, Walid Dabbous. Conference on Emerging Network Experiment and Technology, 2011

344 citations recorded by the source corpus.

Video streaming represents a large fraction of Internet traffic. Surprisingly, little is known about the network characteristics of this traffic. In this paper, we study the network characteristics of the two most popular video streaming services, Netflix and YouTube. We show that the streaming strategies vary with the type of the application (Web browser or native mobile application), and the type of container (Silverlight, Flash, or HTML5) used for video streaming. In particular, we identify three different streaming strategies that produce traffic patterns from non-ack clocked ON-OFF cycles to bulk TCP transfer. We then present an analytical model to study the potential impact of these streaming strategies on the aggregate traffic and make recommendations accordingly.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/b3766fb658863f95ad99c1b874bb1020847f3e03

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Arash Habibi Lashkari
2. Ali Akbar Ghorbani
3. Brandon Heller
4. Nikhil Handigol
5. D. Towsley
6. Nick McKeown
7. M. Shafiq
8. Lusheng Ji

In Computer Vision and Pattern Recognition

1. Ali Akbar Ghorbani
2. D. Towsley
3. Nick McKeown
4. Lusheng Ji
5. Ramesh Johari
6. Alex X. Liu
7. Te-Yuan Huang

Citations in the corpus

• Improving fairness, efficiency, and stability in HTTP-based adaptive video streaming with FESTIVE (2012, neutral): “, [15, 19, 40, 44]).”
• Confused, timid, and unstable: picking a video streaming rate is hard (2012, methodology): “Other work looks at network characteristics of video streaming traffic, rather than focusing on the client or viewer experiences [11, 19, 24].”
• Characterization of Encrypted and VPN Traffic using Time-related Features (2016, background): “In (Rao et al., 2011), Rao et al. propose a network characteristics model for two of the most most popular video streaming services, Netflix and YouTube.”
• Understanding the impact of network dynamics on mobile video user engagement (2014, background): “Previous work found the top providers that use this protocol behave similarly in wired networks [19].”
• A measurement-based study of MultiPath TCP performance over wireless networks (2013, background): “Thus it important to understand how the use of MPTCP might benefit such applications.”