streaming

Video: Low-latency DASH Streaming Using Open Source Tools

Posted on by Russell Trafford-Jones

Low Latency Dash also known as LL-DASH is a modification of MPEG DASH to allow it to operate with close to two seconds’ latency bringing it down to meet, or beat, standard broadcast signals.

Brightcove’s Bo Zhang starts by outlining the aims and methods of getting there. For instance, he explains, the HTTP 1.1 Chunked Transfer element is key to low-latency streaming as it allows the server to start sending a video segment as its being written, not waiting until the file is complete. LL-DASH also has the ability to state an availability window (‘availabilityTimeOffset’).

As LL-MPEG DASH is a living standard, there are updates on the way: Resync points will allow a player to receive a list of places where it can join a stream using SAP types in the ISO-BMFF spec, the server can send a ‘service description’ to the player which can use the information to adjust its latency. Event messages can now be inserted in the middle of segments.

Bo then moves on to explain that he and the team have set up and experiment to gain experience with LL-DASH and test overall latency. He shows that they decided to stream RTMP out of OBS, into a github project called ‘node-gpac-dash’ then to the dash.js player all. between Boston and Seattle. This test runs at 800×600, 30fps with a bitrate of 2.5Mbps and shows results of between 2.5 and 5 seconds depending on the network conditions.

As Bo moves towards the Q&A, he says that low-latency streaming is less scalable because a TCP connection needs to be kept open between the player and the CDN which is a burden.
Another compromise is that smaller chunk sizes in LL-DASH give reduced latency but IO increases meaning sometimes you may have to increase the chunk sizes (and hence latency of the stream) to allow for better performance. He also adds that adverts are more difficult with low-latency streams due to the short amount of time to request and receive the advertising.

Watch now!</a
More detail about the experiments in this talk can be found in Bo’s blog post.
Speakers

Bo Zhang Bo Zhang
Staff Video System Engineer, Research
Brightcove

Video: AV1 Commercial Readiness Panel

Posted on by Russell Trafford-Jones

With two years of development and deployments under its belt, AV1 is still emerging on to the codec scene. That’s not to say that it’s no in use billions of times a year, but compared to the incumbents, there’s still some distance to go. Known as very slow to encode and computationally impractical, today’s panel is here to say that’s old news and AV1 is now a real-time codec.

Brought together by Jill Boyce with Intel, we hear from Amazon, Facebook, Googles, Amazon, Twitch, Netflix and Tencent in this panel. Intel and Netflix have been collaborating on the SVT-AV1 encoder and decoder framework for two years. The SVT-AV1 encoder’s goal was to be a high-performance and scalable encoder and decoder, using parallelisation to achieve this aim.

Yueshi Shen from Amazon and Twitch is first to present, explaining that for them, AV1 is a key technology in the 5G area. They have put together a 1440p, 120fps games demo which has been enabled by AV1. They feel that this resolution and framerate will be a critical feature for Twitch in the next two years as computer games increasingly extend beyond typical broadcast boundaries. Another key feature is achieving an end-to-end latency of 1.5 seconds which, he says, will partly be achieved using AV1. His company has been working with SOC vendors to accelerate the adoption of AV1 decoders as their proliferation is key to a successful transition to AV1 across the board. Simultaneously, AWS has been adding AV1 capability to MediaConvert and is planning to continue AV1 integration in other turnkey content solutions.

David Ronca from Facebook says that AV1 gives them the opportunity to reduce video egress bandwidth whilst also helping increase quality. For them, SVT-AV1 has brought using AV1 into the practical domain and they are able to run AV1 payloads in production as well as launch a large-scale decoder test across a large set of mobile devices.

Matt Frost represent’s Google Chrome and Android’s point of view on AV1. Early adopters, having been streaming partly using AV1 since 2018 in resolution small and large, they have recently added support in Duo, their Android video-conferencing application. As with all such services, the pandemic has shown how important they can be and how important it is that they can scale. Their move to AV1 streaming has had favourable results which is the start of the return on their investment in the technology.

Google’s involvement with the Alliance for Open Media (AOM), along with the other founding companies, was born out of a belief that in order to achieve the scales needed for video applications, the only sensible future was with cheap-to-deploy codecs, so it made a lot of sense to invest time in the royalty-free AV1.

Andrey Norkin from Netflix explains that they believe AV1 will bring a better experience to their members. Netflix has been using AV1 in streaming since February 2020 on android devices using a software decoder. This has allowed them to get better quality at lower bitrates than VP9 Testing AV1 on other platforms. Intent on only using 10-bit encodes across all devices, Andrey explains that this mode gives the best efficiency. As well as being founding members of AoM, Netflix has also developed AVIF which is an image format based on AV1. According to Andrey, they see better performance than most other formats out there. As AVIF works better with text on pictures than other formats, Netflix are intending to use it in their UI.

Tencent’s Shan Liu explains that they are part of the AoM because video compression is key for most Tencent businesses in their vast empire. Tencent cloud has already launched an AV1 transcoding service and support AV1 in VoD.

The panel discusses low-latency use of AV1, with Dave Ronca explaining that, with the performance improvements of the encoder and decoders along-side the ability to tune the decode speed of AV1 by turning on and off certain tools, real-time AV1 are now possible. Amazon is paying attention to low-end, sub $300 handsets, according to Yueshi, as they believe this will be where the most 5G growth will occur so site recent tests showing decoding AV1 in only 3.5 cores on a mobile SOC as encouraging as it’s standard to have 8 or more. They have now moved to researching battery life.

The panel finishes with a Q&A touching on encoding speed, the VVC and LCEVC codecs, the Sisvel AV1 patent pool, the next ramp-up in deployments and the roadmap for SVT-AV1.

Watch now!
Please note: After free registration, this video is located towards the bottom of the page
Speakers

Yueshi Shen Yueshi Shen
Principle Engineer
AWS & Twitch
David Ronca David Ronca
Video Infrastructure Team,
Facebook
Matt Frost Matt Frost
Product Manager, Chome Media Technologies,
Google
Andrey Norkin Andrey Norkin
Emerging Technologies Team
Netflix
Shan Liu Dr Shan Liu
Chief Scientist & General Manager,
Tencent Media Lab
Jill Boyce Jill Boyce
Intel

Video: Real-time AV1 in WebRTC

Posted on by Russell Trafford-Jones

AV1 seems to be shaking off its reputation for slow encoding, now only 2x slower than HEVC. How practical, then is it to put AV1 into a real-time codec aiming for sub-second latency? This is exactly what the Alliance for Open Media are working on as parts of AV1 are perfectly suited for the use case.

Dr Alex from CoSMo Software took the podium at the Alliance for Open Media Research Symposium to lay out the whys and wherefores of updating WebRTC to deliver AV1. He started by outlining the different requirements of real-time vs VoD. With non-live content, encoding time is often unrestricted allowing for complex encoding methods to achieve lower bitrates. Even live CMAF streams aiming to achieve a relatively low 3-second latency have time enough for much more complex encoding than real-time. Encoding, ingest, storage and delivery can all be separated into different parts of the workflow for VoD, whereas real-time is forced to collapse logical blocks down as much as possible. Unsurprisingly, Dr Alex outlines latency as the most important driver in the WebRTC use case.

When streaming, ABR isn’t quite as simple as with chunked formats. The different bit rate streams need to be generated at the encoder to save any transcoding delays. There are two ways of delivering these streams. One is to deliver them as separate streams, the other is to deliver only one, layered stream. The latter method is known as Scalable Video Coding (SVC) which sends a base layer of a low-resolution version of the video which can be decoded on its own. Within that stream, is also the information which builds on top of that video to create a higher-resolution version of the same stream. You can have multiple layers and hence provide information for 3, 4 or more streams.

Managing which streams get to the decoder is done through an SFU (Selective Forwarding Unit) which is a server to which WebRTC clients connect to receive just the stream, or parts of a stream, they need for their current bandwidth capability. It’s important to remember that compared to video conferencing solutions based on WebRTC, that streaming using WebRTC scales linearly. Whilst it’s difficult to hold a meeting with 50 people in a room, it’s possible to optimise what video is sent to everyone by only showing the last 5 speakers in full resolution, the others as thumbnails. Such optimisations are not available for video distribution, rather SFUs and media servers need to be scaled and cascaded. This should be simple, but testing can be difficult but it’s necessary to ensure quality and network resilience at scale.

Cisco have already demonstrated the first real-time AV1-based WebRTC system, though without SVC support. Work is ongoing to deliver improvements to RTP encapsulation of AV1 in WebRTC. For instance, providing Decoding Target Information which embeds information about frames without needing to decode the video itself. This information explains how important each frame is and how it relates to the other video. Such metadata can be used by the SFU or the decoder to understand which frames to drop and send/decode.

Watch now!
Download the slides
Speaker

Alex Gouaillard Dr Alex Gouaillard
Video Codec Working Group – Real-time subgroup, Allience for Open Media
Founder, Directory & CEO, CoSMo Software Consulting Pte. Ltd.
Co-founder & CTO, Millicast

Video: Making a case for DVB-MABR

Posted on by Russell Trafford-Jones

Multicast ABR (mABR) is a way of delivering traditional HTTP-based streams like HLS and DASH over multicast. On a managed telco network, the services are multicast to thousands of homes and only within the home itself does the stream gets converted back unicast HTTP. Devices in the home then access streaming services in exactly the same way as they would Netflix or iPlayer over the internet, but the content is served locally. Streaming is a point-to-point service so each device takes its own stream. If you have 3 devices in the home watching a service, you’ll be sending 3 streams out to them. With mABR, the core network only ever sees one stream to the home and the linear scaling is done internally. Not only does this help remove peaks in traffic, but it significantly reduces the load on the upstream networks, the origin servers and smooths out the bandwidth use.

This video from DVB lays out the business cases which are enabled by mABR. mABR has approved the specification which is now going for standardisation within ETSI. It’s already gained some traction with deployments in the field, so this talk looks at what the projects that drive the continued growth in mABR may look like.

Williams Tovar starts first by making the case for OTT over satellite. With OTT services continuing to take viewing time away from traditional broadcast services, satellite providers are working to ensure they retain relevance and offer value. Delivering these OTT services is, thus, clearly beneficial, but why would you want to? On top of the mABR benefits briefly outlined above, this business case recognises that not everyone is served by a good internet connection. Distributing OTT by satellite can provide high bitrate, OTT experiences to areas with bad broadband and could also be an efficient way to deliver to large public places such as hotels and ships.

Julian Lemotheux from Orange presents a business case for next-generation IPTV. The idea here is to bring down the cost of STBs by replacing CA security with DRM and replacing the chipset with a cheaper one which is less specialised. As DASH and HLS streaming are cpu-based tasks and well understood, general, mass-produced chipsets can be used which are cheaper and removing CA removes some hardware from the box. Also to be considered is that the OTT ecosystem is continually seeing innovation so delivering services in the same format allows providers to keep their offerings up to date without custom development in the IPTV software stack.

Xavier Leclercq from Broadpeak looks, next, at Scaling ABR Delivery. This business case is a consideration of what the ultimate situation will be regarding MPEG2 TSes and ABR. Why don’t we provide all services as Netflix-style ABR streams? One reason is that the scale is enormous with one connection per device, CDNs and national networks would still not be able to cope. Another is that the QoS for MPEG2 transport streams is very good and, whilst it is possible to have bad reception, there is little else that causes interruption to the stream.

mABR can address both of these challenges. By delivering one stream to each home and having the local gateway do the scaling, mass delivery of streamed content becomes both predictable and practical. Whilst there is still a lot of bandwidth involved, the predictable load on the CDNs is much more controlled and with lower peaks, the CDN cost is reduced as this is normally based on the maximum throughput. mABR can also be delivered with a higher QoS than public internet traffic which allows it to benefit from better reliability which could move it in the realm of the traditional transport-stream based serviced. Xavier explains that if you put the gateway within a TV, you are able to deliver a set-top-box-less service whilst if you want to address all devices in you home, you can provide a separate gateway.

Before the video finishes with a Q&A session, Williams delivers the business case for Backhauling over Satellite for CDNs and IP backhaul for 5G Networks. The use case for both has similarities. The CDN backhauling example looks at using satellite to efficiently deliver directly to CDN PoPs in hard to reach areas which may have limited internet links. The Satellite could deliver a high bandwidth set of streams to many PoPs. A similar issue presents itself as there is so much bandwidth available, there is a concern about getting enough into the transmitter. Whether by satellite or IP Multicast, mABR could be used for CDN backhauling to 5G networks delivering into a Mobile Edge Computing (MEC) cache. A further benefit in doing this is avoiding issues with CDN and core network scalability where, again, keeping the individual requests and streams away from the CDN and the network is a big benefit.

Watch now!
Download the slides from this video
Speakers

Williams Tovar Williams Tovar
Soultion Pre-sales manager,
ENENSYS Technologies
Julien Lemotheux Julien Lemotheux
Standardisation Expert,
Orange Labs
Xavier Leclercq Xavier Leclercq
VP Business Development,
Broadpeak
Christophe Berdinat Moderator: Christophe Berdinat
Chairman CM-I MABR, DVB
Innovation and Standardisation Manager, ENENSYS