Adaptive bitrate streaming

Adaptive bitrate streaming is a technique used in streaming multimedia over computer networks.

While in the past most video or audio streaming technologies utilized streaming protocols such as RTP with RTSP, today's adaptive streaming technologies are based almost exclusively on HTTP, and are designed to work efficiently over large distributed HTTP networks.

Adaptive bitrate streaming works by detecting a user's bandwidth and CPU capacity in real time, adjusting the quality of the media stream accordingly. It requires the use of an encoder which encodes a single source media (video or audio) at multiple bit rates. The player client switches between streaming the different encodings depending on available resources. This results in providing very little buffering, faster start times and a good experience for both high-end and low-end connections.

More specifically, adaptive bitrate streaming is a method of video streaming over HTTP where the source content is encoded at multiple bit rates. Each of the different bit rate streams are segmented into small multi-second parts. The segment size can vary depending on the particular implementation, but they are typically between two and ten seconds. First, the client downloads a manifest file that describes the available stream segments and their respective bit rates. During stream start-up, the client usually requests the segments from the lowest bit rate stream. If the client finds that the network throughput is greater than the bit rate of the downloaded segment, then it will request a higher bit rate segment. Later, if the client finds that the network throughput has deteriorated, it will request a lower bit rate segment. An adaptive bitrate (ABR) algorithm in the client performs the key function of deciding which bit rate segments to download, based on the current state of the network. Several types of ABR algorithms are in commercial use: throughput-based algorithms use the throughput achieved in recent prior downloads for decision-making (e.g., throughput rule in dash.js), buffer-based algorithms use only the client's current buffer level (e.g., BOLA in dash.js), and hybrid algorithms combine both types of information (e.g., DYNAMIC in dash.js).

Post-production houses, content delivery networks and studios use adaptive bit rate technology in order to provide consumers with higher quality video using less manpower and fewer resources. The creation of multiple video outputs, particularly for adaptive bit rate streaming, adds great value to consumers. If the technology is working properly, the end user or consumer's content should play back without interruption and potentially go unnoticed. Media companies have been actively using adaptive bit rate technology for many years now and it has essentially become standard practice for high-end streaming providers, permitting little buffering when streaming high-resolution feeds (begins with low-resolution and climbs).

Traditional server-driven adaptive bitrate streaming provides consumers of streaming media with the best-possible experience, since the media server automatically adapts to any changes in each user's network and playback conditions. The media and entertainment industry also benefit from adaptive bitrate streaming. As the video space grows, content delivery networks and video providers can provide customers with a superior viewing experience. Adaptive bitrate technology requires additional encoding, but simplifies the overall workflow and creates better results.

HTTP-based adaptive bitrate streaming technologies yield additional benefits over traditional server-driven adaptive bitrate streaming. First, since the streaming technology is built on top of HTTP, contrary to RTP-based adaptive streaming, the packets have no difficulties traversing firewalls and NAT devices. Second, since HTTP streaming is purely client-driven, all adaptation logic resides at the client. This reduces the requirement of persistent connections between server and client application. Furthermore, the server is not required to maintain session state information on each client, increasing scalability. Finally, existing HTTP delivery infrastructure, such as HTTP caches and servers, can be seamlessly adopted.

A scalable CDN is used to deliver media streaming to an Internet audience. The CDN receives the stream from the source at its Origin server, then replicates it to many or all of its Edge cache servers. The end-user requests the stream and is redirected to the "closest" Edge server. This can be tested using libdash and the Distributed DASH (D-DASH) dataset, which has several mirrors across Europe, Asia and the US. The use of HTTP-based adaptive streaming allows the Edge server to run a simple HTTP server software, whose license cost is cheap or free, reducing software licensing cost, compared to costly media server licences (e.g., Adobe Flash Media Streaming Server). The CDN cost for HTTP streaming media is then similar to HTTP web caching CDN cost.