For or against Adaptive Bit Rate? part II: For ABR

As we have seen here, ABR presents some significant improvements on the way video can be delivered in lossy network conditions.
If we take the fragmented MP4 implementation, we can see that the benefits to a network and content provider are significant. The manifest, transmitted at the establishment of the connection between the player and the server describes the video file, its audio counterpart, its encoding and the different streams and bit rates available.

Since the player has access to all this at the establishment of the connection, it has all the data necessary for an informed decision on the best bit rate to select for the delivery of the video. This is important because ABR is the only technology today that gives the device the control over the selection of the version (and therefore quality and cost) of the video to be delivered.
This is crucial, since there is no efficient means today to convey congestion notification from the Radio Access Network through the Core and Backhaul to the content provider.

Video optimization technology is situated in the Core Network and relies on its reading of the state of the TCP connection (% packet loss, jitter, delay...) to deduce the health of the connection and the cell congestion. The problem, is that a degradation of the TCP connection can have many causes beyond payload congestion. The video optimization server can end up taking decisions to degrade or increase video quality based on insufficient observations or assumptions that might end up contributing to congestion rather than assuage it.

ABR, by providing the device with the capability to decide on the bit rate to be delivered, relies on the device's reading of the connection state, rather than an appliance in the core network. Since the video will be played on the device, this the place where the measurement of the connection state is most accurate.

As illustrated below, as the network conditions fluctuate throughout a connection, the device selects the bit rate that is the most appropriate for the stream, jumping between 300, 500 and 700kbps in this example, to follow network condition.

This provides an efficient means to provide the user with an optimal quality, as network conditions fluctuate, while reducing pressure on congested cells, when the connection degrades.

So, with only 4 to 6% of the traffic, why isn't ABR more widely used and why are network operators implementing video optimization solutions in the core network? Will ABR become the standard for delivering video in lossy networks? These questions and more will be answered in the next post.

For or against Adaptive Bit Rate? part I: what is ABR?

Adaptive Bit Rate streaming (ABR) was invented to enable content providers to provide video streaming services in environment in which bandwidth would fluctuate. The benefit is clear, as a connection capacity changes over time, the video carried over that connection can vary its bit rate, and therefore its size to adapt to the network conditions.The player or client and the server exchange discrete information on the control plane throughout the transmission, whereby the server exposes the available bit rates for the video being streamed and the client selects the appropriate version, based on its reading of the current connection condition.

The technology is fundamental to help accommodate the growth of online video delivery over unmanaged (OTT) and wireless networks.
The implementation is as follow: a video file is encoded into different streams, at different bit rates. The player can "jump" from one stream to the other, as the condition of the transmission degrades or improves. A manifest document is exchanged between the server and the player at the establishment of the connection for the player to understand the list of versions and bit rates available for delivery.

Unfortunately, the main content delivery technology vendors then started to diverge from the standard implementation to differentiate and control better the user experience and the content provider community. We have reviewed some of these vendor strategies here. Below are the main implementations:

• Apple HTTP Adaptive (Live) streaming (HLS) for iPhone and iPad: This version is implemented over HTTP and MPEG2 TS. It uses a proprietary manifest called m3u8. Apple creates different versions of the same streams (2 to 6, usually) and  breaks down the stream into little “chunks” to facilitate the client jumping from one stream to the other. This results in thousands of chunks for each stream, identified through timecode.Unfortunately, the content provider has to deal with the pain of managing thousands of fragments for each video stream. A costly implementation.
• Microsoft IIS Smooth Streaming (Silverlight Windows phone 7): Microsoft has implemented fragmented MP4 (fMP4), to enable a stream to be separated in discrete fragments, again, to allow the player to jump from one fragment to the other as conditions change.  Microsoft uses AAC for audio and AVC/H264 for video compression. The implementation allows to group each video and audio stream, with all its fragments in a single file,  providing a more cost effective solution than Apple's.
• Adobe HTTP Dynamic Streaming (HDS) for Flash: Adobe uses a proprietary format called F4F to allow delivery of flash videos over RTMP and HTTP. The Flash Media Server creates multiple streams, at different bit rate but also different quality levels.  Streams are full lengths (duration of video).

None of the implementations above are inter-operable, from a manifest or from a file perspective, which means that a content provider with one 1080p HD video could see himself creating one version for each player, multiplied by the number of streams to accommodate the bandwidth variation, multiplied by the number of segments, chunks or file for each version... As illustrated above, a simple video can result in 18 versions and thousand of fragments to manage. This is the reason why only 4 to 6% of current videos are transmitted using ABR. The rest of the traffic uses good old progressive download, with no capacity to adapt to changes in bandwidth, which explains in turn why wireless network operators (over 60 of them) have elected to implement video optimization systems in their networks. We will look, in my next posts, at the pros and cons of ABR and the complementary and competing technologies to achieve the same goals.

Find part II of this post here.