I think there is something missing from your model.    I just scanned your paper and noticed that you made no mention of rounding errors, nor some details around the drain phase timing,   The implementation guarantees that the actual average rate across the combined BW probe and drain is strictly less than the measured maxBW and that the flight size comes back down to minRTT*maxBW before returning to unity pacing gain.  In some sense these checks are redundant, but If you don't do them, it is absolutely true that you are at risk of seeing divergent behaviors.

That said, it is also true that multi-stream BBR behavior is quite complicated and needs more queue space than single stream.   This

complicates the story around the traditional workaround of using multiple streams to compensate for Reno & CUBIC lameness at larger scales (ordinary scales today).    Multi-stream does not help BBR throughput and raises the queue occupancy, to the detriment of other users.

And yes, in my presentation, I described the core BBR algorithms as a framework, which might be extended to incorporate many additional algorithms if they provide optimal control in some settings.  And yes, several are present in BBRv2.

Ok, thanks for clarification.

Regards,
 Roland

 

Thanks,

--MM--
The best way to predict the future is to create it.  - Alan Kay

We must not tolerate intolerance;

       however our response must be carefully measured: 

            too strong would be hypocritical and risks spiraling out of control;

            too weak risks being mistaken for tacit approval.

On Thu, Jul 8, 2021 at 4:24 AM Bless, Roland (TM) <roland.bless@kit.edu> wrote:

Hi Matt,

On 08.07.21 at 00:38 Matt Mathis wrote:

Actually BBR does have a window based backup, which normally only comes into play during load spikes and at very short RTTs.   It defaults to 2*minRTT*maxBW, which is twice the steady state window in it's normal paced mode.

So yes, BBR follows option b), but I guess that you are referring to BBRv1 here.
We have shown in [1, Sec.III] that BBRv1 flows will always run (conceptually) toward their above quoted inflight-cap of
2*minRTT*maxBW, if more than one BBR flow is present at the bottleneck. So strictly speaking " which normally only comes
into play during load spikes and at very short RTTs" isn't true for multiple BBRv1 flows.

It seems that in BBRv2 there are many more mechanisms present
that try to control the amount of inflight data more tightly and the new "cap"
is at 1.25 BDP.

This is too large for short queue routers in the Internet core, but it helps a lot with cross traffic on large queue edge routers.

Best regards,
 Roland

[1] https://ieeexplore.ieee.org/document/8117540

On Wed, Jul 7, 2021 at 3:19 PM Bless, Roland (TM) <roland.bless@kit.edu> wrote:

Hi Matt,

[sorry for the late reply, overlooked this one]

please, see comments inline.

On 02.07.21 at 21:46 Matt Mathis via Bloat wrote:

The argument is absolutely correct for Reno, CUBIC and all other self-clocked protocols.  One of the core assumptions in Jacobson88, was that the clock for the entire system comes from packets draining through the bottleneck queue.  In this world, the clock is intrinsically brittle if the buffers are too small.  The drain time needs to be a substantial fraction of the RTT.

I'd like to separate the functions here a bit:

1) "automatic pacing" by ACK clocking

2) congestion-window-based operation

I agree that the automatic pacing generated by the ACK clock (function 1) is increasingly
distorted these days and may consequently cause micro bursts.
This can be mitigated by using paced sending, which I consider very useful.
However, I consider abandoning the (congestion) window-based approaches
with ACK feedback (function 2) as harmful:
a congestion window has an automatic self-stabilizing property since the ACK feedback reflects
also the queuing delay and the congestion window limits the amount of inflight data.
In contrast, rate-based senders risk instability: two senders in an M/D/1 setting, each sender sending with 50%
bottleneck rate in average, both using paced sending at 120% of the average rate, suffice to cause
instability (queue grows unlimited).

IMHO, two approaches seem to be useful:
a) congestion-window-based operation with paced sending
b) rate-based/paced sending with limiting the amount of inflight data

However, we have reached the point where we need to discard that requirement.  One of the side points of BBR is that in many environments it is cheaper to burn serving CPU to pace into short queue networks than it is to "right size" the network queues.

The fundamental problem with the old way is that in some contexts the buffer memory has to beat Moore's law, because to maintain constant drain time the memory size and BW both have to scale with the link (laser) BW.

See the slides I gave at the Stanford Buffer Sizing workshop december 2019: Buffer Sizing: Position Paper 

Thanks for the pointer. I don't quite get the point that the buffer must have a certain size to keep the ACK clock stable:
in case of an non application-limited sender, a very small buffer suffices to let the ACK clock
run steady. The large buffers were mainly required for loss-based CCs to let the standing queue
build up that keeps the bottleneck busy during CWnd reduction after packet loss, thereby
keeping the (bottleneck link) utilization high.

Regards,

 Roland

Note that we are talking about DC and Internet core.  At the edge, BW is low enough where memory is relatively cheap.   In some sense BB came about because memory is too cheap in these environments.

Thanks,

--MM--
The best way to predict the future is to create it.  - Alan Kay

We must not tolerate intolerance;

       however our response must be carefully measured: 

            too strong would be hypocritical and risks spiraling out of control;

            too weak risks being mistaken for tacit approval.

On Fri, Jul 2, 2021 at 9:59 AM Stephen Hemminger <stephen@networkplumber.org> wrote:

On Fri, 2 Jul 2021 09:42:24 -0700
Dave Taht <dave.taht@gmail.com> wrote:

> "Debunking Bechtolsheim credibly would get a lot of attention to the
> bufferbloat cause, I suspect." - dpreed
>
> "Why Big Data Needs Big Buffer Switches" -
> http://www.arista.com/assets/data/pdf/Whitepapers/BigDataBigBuffers-WP.pdf
>

Also, a lot depends on the TCP congestion control algorithm being used.
They are using NewReno which only researchers use in real life.

Even TCP Cubic has gone through several revisions. In my experience, the
NS-2 models don't correlate well to real world behavior.

In real world tests, TCP Cubic will consume any buffer it sees at a
congested link. Maybe that is what they mean by capture effect.

There is also a weird oscillation effect with multiple streams, where one
flow will take the buffer, then see a packet loss and back off, the
other flow will take over the buffer until it sees loss.

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