[tsvwg] What is "Scalable Congestion Control" in L4S?

Vasilenko Eduard <vasilenko.eduard@huawei.com> Tue, 16 April 2024 08:26 UTC

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From: Vasilenko Eduard <vasilenko.eduard@huawei.com>
To: "tsvwg@ietf.org" <tsvwg@ietf.org>
Thread-Topic: What is "Scalable Congestion Control" in L4S?
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Date: Tue, 16 Apr 2024 08:25:52 +0000
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Subject: [tsvwg] What is "Scalable Congestion Control" in L4S?
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Hi all,

Both RFCs (9332, 9330) gives a formal definition that:
"Scalable Congestion Control: A congestion control where the average time from one congestion signal to the next (the recovery time) remains invariant as flow rate scales, all other factors being equal."
It is just a rate of the congestion signal, a simple matter.

RFC 9332 section 2.1 gives the impression that Scalable Congestion Control has more fundamental differences:
"the steady-state cwnd of Reno is inversely proportional to the square root of p" (drop probability)
But
"A supporting paper [https://dl.acm.org/doi/10.1145/2999572.2999578] includes the derivation of the equivalent rate equation for DCTCP, for which cwnd is inversely proportional to p (not the square root), where in this case p is the ECN-marking probability. DCTCP is not the only congestion control that behaves like this, so the term 'Scalable' will be used for all similar congestion control behaviours". Then in section 1.2 we see the BBR in the list of "Scalable CCs".

1. The formal definition of "Scalable CC" looks wrong. At least it contradicts section 2.1.
2. It is difficult to believe that BBR and CUBIC/RENO have so different reactions to overload signals because they both play fairly (starting from BBRv2) in one queue as demonstrated in many tests. It is probably impossible for such different sessions to share the load fairly if one session is reacting to p, but the other is reacting to the square root from p (p is the probability for congestion signal).

Best Regards
Eduard Vasilenko
Senior Architect
Network Algorithm Laboratory
Tel: +7(985) 910-1105