Re: RTP over QUIC experiments

Vidhi Goel <vidhi_goel@apple.com> Fri, 12 November 2021 23:44 UTC

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From: Vidhi Goel <vidhi_goel@apple.com>
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Subject: Re: RTP over QUIC experiments
Date: Fri, 12 Nov 2021 15:43:57 -0800
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Cc: "avt@ietf.org" <avt@ietf.org>, IETF QUIC WG <quic@ietf.org>, Ingemar Johansson S <ingemar.s.johansson@ericsson.com>
To: Ingemar Johansson S <ingemar.s.johansson=40ericsson.com@dmarc.ietf.org>, "mathis.engelbart@gmail.com" <mathis.engelbart@gmail.com>, "ott@in.tum.de" <ott@in.tum.de>
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Hello,

Have thoroughly read the RTP over QUIC paper https://www.in.tum.de/fileadmin/w00bws/cm/papers/epiq21-rtp-over-quic.pdf <https://www.in.tum.de/fileadmin/w00bws/cm/papers/epiq21-rtp-over-quic.pdf>

What I am trying to understand is, what is the motivation behind running real time congestion control like SCReAM over QUIC congestion control? The results (as Ingemar also mentioned) are not encouraging.
If we want to use a single QUIC connection for media (audio/video using RTP) and other reliable streams, then would it be better to not use QUIC CC for media streams and only use it for reliable streams? Obviously this will violate the current spec which applies congestion control on connection level. But maybe this use case can be specialized.

> + Split of network congestion control and media rate control : QUIC already today has the congestion control on the connection level, it is then up to the individual streams to deliver media, subject to the individual stream priorities. SCReAM is quite similar in that respect, one difference is perhaps the implementation of the media rate control.  

> I think that with QUIC one should do a full split and do the network congestion control on the QUIC connection level. The congestion control would then be some low latency version, perhaps BBRv2? or something similar, I am not sure that the network congestion control in SCReAM is the idea choice here as it is quite a lot tailored for RTP media. 

The impact of cascading two congestion controllers (with different input and output parameters) has not been studied extensively yet. And is a real time CC like SCReAM by itself not enough to control the congestion in the network? In other words, does it need another congestion controller to make sure that the real time data doesn’t cause more congestion in the network?


> My SCReAM experience is that one need to leak some of the congestion signals from the connection level congestion control up to the stream rate control, to make the whole thing responsive enough. In the SCReAM code one can see that the exotic variable queueDelayTrend as well as ECN marks and loss events are used for this purpose. I believe that something like that is needed for an RTP (or whatever low latency) media over QUIC. I believe that it is necessary to leak congestion information from the connection level up to the stream level, especially to be able to exploit L4S fully, even though it is a bit of a protocol layer violation.
We absolutely should allow sharing of network events, like RTT, ECN, packet loss from QUIC to RTP. Not sure how it is protocol layer violation.


> + Page 18 : Inferring the receive timestamp. What is suspect is that you will essentially halve the estimated queue delay (I assume here that the reverse path is uncongested). One alternative could be to compute 
> receive-ts = send-ts + latest_rtt + min_rtt
> where min_rtt is the min RTT over a given time interval

You are right that halving latest_rtt / 2 may not be accurate if the reverse path is not congested, but there is no guarantee for that. So, a more accurate way to compute receive-ts is to use One way timestamps which can be added to QUIC as new Frames.


Thanks,
Vidhi


> On Nov 12, 2021, at 8:28 AM, Ingemar Johansson S <ingemar.s.johansson=40ericsson.com@dmarc.ietf.org> wrote:
> 
> Hi Jörg, Mathis + others
>  
> It was nice to learn about your activity to try and use SCReAM as example algorithm to integrate with QUIC. Pages 14-25 in
> https://datatracker.ietf.org/meeting/112/materials/slides-112-avtcore-ietf-112-avtcore-03 <https://datatracker.ietf.org/meeting/112/materials/slides-112-avtcore-ietf-112-avtcore-03>
> Did you use the new gsteamer plugin from https://github.com/EricssonResearch/scream/tree/master/gstscream <https://github.com/EricssonResearch/scream/tree/master/gstscream>  ?
>  
> Observations/Comments: 
> + SCReAM + Reno : Strange that the throughput dropped like that but perhaps an unlucky outcome of two cascaded congestion controls. 
>  
> + Split of network congestion control and media rate control : QUIC already today has the congestion control on the connection level, it is then up to the individual streams to deliver media, subject to the individual stream priorities. SCReAM is quite similar in that respect, one difference is perhaps the implementation of the media rate control.  
> I think that with QUIC one should do a full split and do the network congestion control on the QUIC connection level. The congestion control would then be some low latency version, perhaps BBRv2? or something similar, I am not sure that the network congestion control in SCReAM is the idea choice here as it is quite a lot tailored for RTP media. 
> The media rate control is done on the stream level and is then subject to stream priority. This should give a more clean split of functionality. 
> My SCReAM experience is that one need to leak some of the congestion signals from the connection level congestion control up to the stream rate control, to make the whole thing responsive enough. In the SCReAM code one can see that the exotic variable queueDelayTrend as well as ECN marks and loss events are used for this purpose. I believe that something like that is needed for an RTP (or whatever low latency) media over QUIC. I believe that it is necessary to leak congestion information from the connection level up to the stream level, especially to be able to exploit L4S fully, even though it is a bit of a protocol layer violation.
>  
> + Stream prioritization : … is a problematic area, especially if one stream is low latency video and another stream is a large chunk of data for e.g. a large web page. With a simple round robin scheduler, the stream with the large chunk of data will easily win because it is quite likely to always have data to transmit. So some WRR is needed. I have even had problems with the algorithm in SCReAM that prioritizes between two cameras/video coders, this because the two cameras see different views and thus provide differing information content/compression need.
>  
> + Page 18 : Inferring the receive timestamp. What is suspect is that you will essentially halve the estimated queue delay (I assume here that the reverse path is uncongested). One alternative could be to compute 
> receive-ts = send-ts + latest_rtt + min_rtt
> where min_rtt is the min RTT over a given time interval
>  
>  
> Regards
> /Ingemar