As video becomes one of the most demanding services for network traffic and Internet video becomes an important part of modern life, the quality of experience needs to meet the user’s expectations, regardless of the device or network being used. More and more video is being consumed on smartphones and tablets. The smaller screens allow for lower bit-rates, but the video playback need to start quickly and remain smooth throughout.
Internet Video delivery is challenging because of factors such as high bitrates and sensitivity to delay or packet loss.
In the past, video streaming was typically associated to RTSP, with RTP used for transmission. This protocol uses “VCR-like” commands such as PLAY and PAUSE. In this scheme, the server has to keep track of the client’s state. The server starts playing a stream when giving the PLAY command, and has to maintain the state of each session in order to know what packet to send next. The video stream is based on a single “track”, a file with a fixed encoding profile that cannot change. The quality would quickly suffer when there was a shortage of bandwidth such as congestion leading to packet loss.
Today, HTTP based adaptive streaming services provide a more efficient means of delivery over the Internet. Similarly to RTSP, the video stream can start playing out before the entire file has been downloaded. The main advantage of adaptive streaming however is that it allows the end point to adjust to changes in available bandwidth and delay.
Apple’s HTTP Live Streaming, SilverLight Smooth Streaming from Microsoft and Adobe’s HTTP Dynamic Streaming are notable examples of this technology. These applications manage a set of tracks, each with a different bit rate. The tracks are then divided into small segments (typically 2 seconds) for distribution to a wide variety of different display profiles.
The main innovation here is that if an endpoint sees a dynamic change in bandwidth (up or down) it can react by changing “tracks” to a higher- or lower-bandwidth track, offering the optimal quality. With a limited amount of local buffering the end point can guarantee an acceptable user experience. The popularity of commercial adaptive streaming applications proves that the quality is critical for Internet video.
Unlike traditional streaming protocols, HTTP based progressive download offers “smooth” video transmission. These streaming techniques are very effective for stored premium content. In these scenarios, the content is encoded into multiple tracks “off-line” and then placed on the server for consumption. It is less useful for user-generated content, were the number of video clips is orders of magnitudes larger (think of YouTube for example). In those situations, it makes more sense to adapt the bandwidth on the fly for the requested clip (see below).
Video delivery Network
We’ve discussed video delivery from the point of view of the client and the server. The network infrastructure in between is another key factor in efficient delivery. Reducing the data sent by a central server to many clients will significantly reduce the possibility of congestion and packet loss. Multicasting, distributing and caching the data to edge nodes is an efficient way to reduce the original data throughput requirement from the central server. The edge node may also be responsible for dynamically adapting the content to the different profiles required by various terminal devices.
The Content Delivery Network (CDN) model is often used for Internet video delivery. In a CDN, the video source or stream originates from a file server or broadcast TV headend. Popular video streams are stored (cached) at many or all of the CDN edge nodes. When a client requests the stream, it will be transparently redirected to the “closest” edge node. CDN architectures and optimization are quite an elaborate topic that we’ll save for another post.
CDNs help alleviate congestion in the core of a network like the public internet. However with the popularity of mobile video, the problem is slightly different. We not only need to reduce congestion in the core network, we now need to reduce congestion on the wireless link as well. To solve this problem we’re seeing edge routers become more sophisticated. Edge routers aimed at wireless deployments now have embedded DSP capabilities to do inline transrating: they can dynamically change the video bitrate to reduce it when network congestion occurs. These routers perform deep packet inspection (DPI) to determine that the contents are video, and then redirect the media to a DSP for dynamic transcoding/transrating.
As video continues to consume a larger and larger percentage of mobile data traffic, the combination of adaptive streaming, CDNs and inline transrating will become commonplace. In future posts we’ll go into more detail of each of these technologies.
Hui Pang is a Field Application Engineer at Octasic Inc. Mr. Pang has over 10 years of telecommunications experience. Prior to Octasic, he was a Firmware Engineer at BlueTree Wireless Data and also worked for Nortel Networks. Pang received his B. Eng from Beijing Institute of Technology and also has a Masters in Electrical and Computer Engineering from Concordia University.
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