Network Characteristics of Video Streaming Traffic

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.

Generic
								      behavior (traffic pattern) during a video streaming session
Generic behavior during a typical video streaming session.

During a typical streaming session, the video content is transferred in two phases: a buffering phase followed by a steady state phase. During the buffering phase, the data transfer rate is limited by the end-to-end available bandwidth. The video player begins playback when a sufficient amount of data is available in its buffer. Video playback does not wait for the buffering phase to end. In the steady state phase, the average download rate is slightly larger than video encoding rate. This average download rate in the steady state phase is achieved by periodically transferring one block of video content. These periodic transfers produce cycles of ON-OFF periods. During each ON period, a block of data is transferred at the end-to-end available bandwidth that can be used by TCP; the TCP connection is idle during the OFF periods. We use the existence of the steady state phase and the technique used to throttle the data transfer rate in the steady state phase to identify the underlying streaming strategy. We observe the following three streaming strategies for Netflix and YouTube videos.

Streaming Strategies for a given combination of Browser and Container.

ServiceYouTubeNetFlix
ContainerFlashHTML5Flash (HD)Silverlight
Internet ExplorerShort ON-OFFShort ON-OFFNo ON-OFFShort ON-OFF
Google ChromeShort ON-OFFLong ON-OFFNo ON-OFFShort ON-OFF
FirefoxShort ON-OFFNo ON-OFFNo ON-OFFShort ON-OFF
iOSNot applicableMultiple Not applicableShort ON-OFF
AndroidNot applicableLong ON-OFFNot applicableLong ON-OFF
[RLB_CONEXT11]
Ashwin Rao, Yeon-sup Lim, Chadi Barakat, Arnaud Legout, Don Towsley, and Walid Dabbous. Network Characteristics of Video Streaming Traffic. In Proc. of ACM CoNEXT'11, Dec. 6--9, 2011, Tokyo, Japan. download
The slide of the CoNEXT presentation can be freely reused. However, the authors would appreciate if you inform them that you intend to use these slides.
The poster presented at CCNxCon'11 is also available for download.

This work was a joint collaboration between researchers at INRIA, Sophia Antipolis and University of Massachusetts, Amherst.

Download the dataset

This dataset contains detail traffic logs of packets exchanged during YouTube and Netflix streaming sessions. Details about the dataset collection are available in the paper [RLB_CONEXT11]. For each streaming session, we used tcpdump to capture the packets exchanged between the streaming server(s) and our client. We then parsed these pcap files to log the packet timestamp, the tcp sequence number, and packet length of each packet exchanged between the streaming server(s) and the client. This dataset comprises of these logs along with other auxilary information that we used to better understand the observed traffic patterns. For ease of download, we have split the dataset in multiple tarball files.

  1. YouTube data

    This tarball contains the YouTube data in the format mentioned in dataset description. Please note that this tarball contains compressed folders.

    Download YouTube data size: 1.5 GB, md5sum: e3062413b80160fe6b9117ca9057ca5f (YouTube.tar)

  2. Netflix data

    This tarball contains the Netflix data in the format mentioned in dataset description. Please note that this tarball contains compressed folders.

    Download Netflix data size: 170 MB, md5sum: 21f844747dbead02c1e4b5b917d434d8 (Netflix.tar)

  3. Parsing scripts

    We also make available the scripts used to generate these datasets. This tarball contains the scripts used to parse the pcap files. Please contact the authors for details on how to use the scripts.

    Download Parsing scripts size: 227 KB, md5sum: 42d7e1d047cfd6aa3b7fc028be21eaee (PcapParsing.tar.bz2)

  4. Matlab scripts

    We use Matlab to further process the datasets. This tarball contains the scripts we used to process the data, the output of the processing, and the matlab scripts to generate the plots present in the paper. Please contact the authors for details on how to use these scripts.

    Download Matlab scripts size: 204 MB, md5sum: 148418916c01fdb7ee65cdfd102a26d0 (MatlabScripts.tar.bz2)

We would really appreciate if you inform us on how you plan to use this dataset. The raw pcap file used to generate this dataset are currently not available due to space constraints. If you require the raw pcap files please send us an email.

Dataset description

The YouTube and Netflix tarballs contain the following file structure and contents.

	  [Location Name]
	  ├── [Container]
	  │   ├── [Browser 1]
	  │   │   ├── contentLengths
	  │   │   ├── downEvolution
	  │   │   ├── parsedIAT
	  │   │   ├── parsedPayloadLens
	  │   │   ├── parsedSeqNums
	  │   │   ├── parseMeta
	  │   │   ├── rcvwndEvolution
	  │   │   ├── seqEvolution
	  │   │   └── streamingIPs
	  │   ├── [Browser 2]
	  │   │   ├── contentLengths
	  │   │   ├── downEvolution
	  │   │   ├── parsedIAT
	  │   │   ├── parsedPayloadLens
	  │   │   ├── parsedSeqNums
	  │   │   ├── parseMeta
	  │   │   ├── rcvwndEvolution
	  │   │   ├── seqEvolution
	  │   │   └── streamingIPs
	

In our paper, we performed our measurements from locations: Home, Research, Residence, and University. Each of these four locations abstracts a network within which we streamed video to different browsers and devices. The YouTube measurements were carried out from each of these four locations while NetFlix measurements were carried out from Home and University. The Home and University locations are in USA while the other two locations, Research and Residence, are in France. The mobile measurements for YouTube were carried out from the location named Research while NetFlix measurements for mobile devices were carried out from the location named University.

YouTube uses Flash and HTML5 as the containers to stream videos while Netflix uses Silverlight as the video container.

The description of each file is as follows.