Thanks Neal. You might want to check out the flows released as iperf 2. Basically instantiate flows and run them. There typically is a controller running python3 (v 3.10 or better) that uses ssh pipes to DUTs. The design is event driven and utilizes python's asyncio which is quite powerful. The DUTs just need iperf2 and ssh.

The code is at an alpha level and we're looking for broader industry support and contributions. Both in realtime plotting but also in things like multivariate regression detection using statistical process controls (SPC) e.g. Hoteling. There is some crude clustering code around latency too which uses Kolmogorov-Smirnov distance matrices per the histograms.

A suggestion is that those in developer and control test roles synchronize their device clocks with PTP. Iperf 2 supports one way delay (OWD) calculations but these only work if the clocks are sync'd.  These in turn can be used per Little's law to calculate effective average queue depth, though this typically assumes a steady state measurement.

Bob 

On Sun, Aug 28, 2022 at 4:54 PM Neal Cardwell <ncardwell@google.com> wrote:

If you are talking about the screenshot of the UI at  https://github.com/google/transperf, yes, that particular test is a simple bulk flow test to show a simple case to give a sense of what the UI looks like. :-)

We use a few different approaches that can examine dynamic flows causing packet loss: 

(1) The test configuration language is Python, so you can construct arbitrarily fancy dynamic flow scenarios with arbitrary numbers of flows starting and stopping at arbitrary times.

(2) The tests can also use netperf command line options to run periodic short transfers. (And we welcome patches to integrate support for other tools.)

(3) We also run a fair number of tests for robustness to loss just using randomly injected packet loss (using netem).

These are just some of the approaches we have used, and I don't claim that these are the only or best approaches to look at this. :-)

cheers,

neal

On Sun, Aug 28, 2022 at 6:39 PM Bob McMahon <bob.mcmahon@broadcom.com> wrote:

Hi Neal,

These look like steady-state bulk flow tests unless I'm missing something.

Bob

On Sun, Aug 28, 2022 at 11:43 AM Neal Cardwell <ncardwell@google.com> wrote:

Sure. For testing these kinds of properties of the BBR algorithm we use various transperf test cases. The transperf tool is something Soheil Hassas Yeganeh and our team cooked up and open-sourced here:

  https://github.com/google/transperf

Best regards,

neal

On Sat, Aug 27, 2022, 4:43 PM Bob McMahon <bob.mcmahon@broadcom.com> wrote:

Curious to what you're doing during development, if you can share?

Thanks,
Bob

On Sat, Aug 27, 2022 at 7:44 AM Neal Cardwell <ncardwell@google.com> wrote:

Hi Bob,

Good question. I can imagine a number of different techniques to generate and measure the traffic flows for this kind of study, and don't have any particular suggestions.

neal

On Fri, Aug 26, 2022 at 4:54 PM Bob McMahon <bob.mcmahon@broadcom.com> wrote:

Hi Neal,

Any thoughts on tooling to generate and measure the traffic flows BBR is designed to optimize? I've been adding some low duty cycle support in iperf 2 with things like --bounceback and --burst-period and --burst-period. We could pull the size and period from a known distribution or distributions though not sure what to pick.

Thanks,
Bob

Bob

On Fri, Aug 26, 2022 at 6:36 AM 'Neal Cardwell' via BBR Development <bbr-dev@googlegroups.com> wrote:

Yes, I agree the assumptions are key here. One key aspect of this paper is that it focuses on the steady-state behavior of bulk flows.

Once you allow for short flows (like web pages, RPCs, etc) to dynamically enter and leave a bottleneck, the considerations become different. As is well-known, Reno/CUBIC will starve themselves if new flows enter and cause loss too frequently. For CUBIC, for a somewhat typical 30ms broadband path with a flow fair share of 25 Mbit/sec, if new flows enter and cause loss more frequently than roughly every 2 seconds then CUBIC will not be able to utilize its fair share. For a high-speed WAN path, with 100ms RTT and fair share of 10 Gbit/sec,  if new flows enter and cause loss more frequently than roughly every 40 seconds then CUBIC will not be able to utilize its fair share. Basically, loss-based CC can starve itself in some very typical kinds of dynamic scenarios that happen in the real world.

BBR is not trying to maintain a higher throughput than CUBIC in these kinds of scenarios with steady-state bulk flows. BBR is trying to be robust to the kinds of random packet loss that happen in the real world when there are flows dynamically entering/leaving a bottleneck.

cheers,

neal

On Thu, Aug 25, 2022 at 8:01 PM Dave Taht via Bloat <bloat@lists.bufferbloat.net> wrote:

I rather enjoyed this one. I can't help but wonder what would happen
if we plugged some different assumptions into their model.

https://www.comp.nus.edu.sg/~bleong/publications/imc2022-nash.pdf

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