Lower Latency, Higher Rewards
By Remi Beaudouin, Chief Strategy Officer, ATEME
As viewership of traditional broadcasts fall and consumers increasingly favour streaming services, lowering latency for live streaming is long overdue. Anyone who has ever streamed a big sports game and heard neighbours celebrate a goal or received a notification on their phone before seeing anything on-screen has suffered at the hands of latency issues. Streaming technologies were typically not designed or implemented with low latency in mind. Particularly for sports, poor latency can result in buffering, reduced video quality and a bad viewing experience. In recent years, there have been multiple examples of this, including last year’s coverage of the World Cup when some streams lagged 30 seconds behind the TV broadcast and this year’s Super Bowl, which had an average delay of 30 to 47 seconds, causing backlash from avid fans. Poor latency can even lead to some viewers switching off completely with new research finding that the average number of times a viewer will let a video re-buffer before they stop watching has dropped 19% from 2.7 times in 2016 to 2.2 times in 2019. Traditionally, the multiple components within the broadcast chain – processing, packaging, streaming and decoding – have added latency. Therefore, in order to reduce latency, each component must be upgraded. This is an area in which the introduction of machine-based processing and the Common Media Application Format (CMAF) are spurring improvement.
What is CMAF?
Let’s start at the end, meaning the packaging. CMAF was first introduced in 2016 when Apple and Microsoft proposed the standard to the Moving Pictures Expert Group (MPEG) with the standard being officially published in January 2018. However, despite the fact it was launched almost two years ago, it is only now beginning to be widely recognised amongst OTT players as live streaming becomes more commonplace and the need to reduce latency becomes more pressing. As a standard, CMAF aims to simplify the delivery of HTTP-based streaming media, which is currently a complex process due to the number of various formats to address. CMAF could be the-one-fitting-all format, there are numerous reviews and debate on this topic.
The ubiquity is not the only advantage of CMAF. Unlike other formats, CMAF has indeed a low-latency mode which enables low-latency streaming. CMAF’s low-latency mode allows the encoder/packager to push video chunks instead of request-based video segment delivery. This process sees the video broken down into smaller chunks of a set duration, which can then be immediately published upon encoding/packaging. This means that near-real-time delivery can take place while later chunks are still processing. While CMAF’s main benefit is considered to be its ability to reduce latency, it also streamlines server efficiency, minimises workflow complexity and cuts costs.
In addition to CMAF, machine learning-based algorithms are being used to make encoding more efficient and reduce the needed buffer – hence latency – while maintaining the same video quality. After all, compression is all about computation. Using machine-learning techniques to optimise/fast-track motion vectors prediction or pixel quantisation makes sense. By using a combination of machine-based encoding and CMAF, it is possible to reduce latency to sub-1 second of latency rather than several 10’s of seconds or more, enough to get on par with OTA, cable and IP deliveries. Consequently, a large number of broadcasters are now deploying upgraded workflows to enable this type of latency. Beyond this, when latency is not a critical factor, Machine-Learning-based encoding can also improve video quality, increasing bandwidth efficiency and the audio encoder.
The rewards of lower latency
Competition within the broadcast market continues to be fierce, with new entertainment players – like Apple TV, Disney + – having recently entered the fray. Consequently, it’s vital broadcasters and service providers going OTT make latency a matter of priority to avoid forcing audiences to switch off and to ensure they reach their potential. This is particularly the case with live sports coverage as research has found that two-thirds (65%) of people aged 26 to 45 would stream more sports online if it was not delayed from the broadcast. Fortunately, implementing machine-learning based encoding and CMAF to reduce latency is a case of upgrading current workflows, rather than requiring broadcasters to overhaul their infrastructure. Thus, more and more content will be made available in low latency, which in turn will foster more players to support it and make for a better viewing experience for audiences”.