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<p>If our business-transaction customers are made miserable by timeouts, by analogy it follows that home internet users are made miserable by</p>
<ul>
<li>stalls, "buffering" and complete disappearance in conference-calls</li><li>"shouting down the well" distortion in any kind of audio</li></ul>
<p>Disappearance is probably disconnection, and easy to measure</p>
<p>The others are delay-related, and can be computed from timestampe and sequence numbers.</p>
<p>Can we provide a tool to expose the latter? A "miserometer"?</p>
<p>--dave<br>
</p>
<p><br>
</p>
<div class="moz-cite-prefix">On 10/23/22 07:57, Sebastian Moeller via Starlink wrote:<br>
</div>
<blockquote type="cite" cite="mid:339AB8BC-9628-40E2-9339-77FCFA74488D@gmx.de">
<pre class="moz-quote-pre" wrap="">Hi Glenn,
</pre>
<blockquote type="cite">
<pre class="moz-quote-pre" wrap="">On Oct 23, 2022, at 02:17, Glenn Fishbine via Rpm <a class="moz-txt-link-rfc2396E" href="mailto:rpm@lists.bufferbloat.net"><rpm@lists.bufferbloat.net></a> wrote:
As a classic died in the wool empiricist, granted that you can identify "misery" factors, given a population of 1,000 users, how do you propose deriving a misery index for that population?
We can measure download, upload, ping, jitter pretty much without user intervention. For the measurements you hypothesize, how you you automatically extract those indecies without subjective user contamination.
I.e. my download speed sucks. Measure the download speed.
My isp doesn't fix my problem. Measure what? How?
Human survey technology is 70+ years old and it still has problems figuring out how to correlate opinion with fact.
Without an objective measurement scheme that doesn't require human interaction, the misery index is a cool hypothesis with no way to link to actual data. What objective measurements can be made? Answer that and the index becomes useful. Otherwise it's just consumer whining.
Not trying to be combative here, in fact I like the concept you support, but I'm hard pressed to see how the concept can lead to data, and the data lead to policy proposals.
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[SM] So it seems that outside of seemingly simple to test throughput numbers*, the next most important quality number (or the most important depending on subjective ranking) is how does latency change under "load". Absolute latency is also important albeit static high latency can be worked around within limits so the change under load seems more relevant.
All of flent's RRUL test, apple's networkQuality/RPM, and iperf2's bounceback test offer methods to asses latency change under load**, as do waveforms bufferbloat tests and even to a degree Ookla's speedtest.net. IMHO something like latency increase under load or apple's responsiveness measure RPM (basically the inverse of the latency under load calculated on a per minute basis, so it scales in the typical higher numbers are better way, unlike raw latency under load numbers where smaller is better).
IMHO what networkQuality is missing ATM is to measure and report the unloaded RPM as well as the loaded the first gives a measure over the static latency the second over how well things keep working if capacity gets tight. They report the base RTT which can be converted to RPM. As an example:
macbook:~ user$ networkQuality -v
==== SUMMARY ====
Upload capacity: 24.341 Mbps
Download capacity: 91.951 Mbps
Upload flows: 20
Download flows: 16
Responsiveness: High (2123 RPM)
Base RTT: 16
Start: 10/23/22, 13:44:39
End: 10/23/22, 13:44:53
OS Version: Version 12.6 (Build 21G115)
Here RPM 2133 corresponds to 60000/2123 = 28.26 ms latency under load, while the Base RTT of 16ms corresponds to 60000/16 = 3750 RPM, son on this link load reduces the responsiveness by 3750-2123 = 1627 RPM a reduction by 100-100*2123/3750 = 43.4%, and that is with competent AQM and scheduling on the router.
Without competent AQM/shaping I get:
==== SUMMARY ====
Upload capacity: 15.101 Mbps
Download capacity: 97.664 Mbps
Upload flows: 20
Download flows: 12
Responsiveness: Medium (427 RPM)
Base RTT: 16
Start: 10/23/22, 13:51:50
End: 10/23/22, 13:52:06
OS Version: Version 12.6 (Build 21G115)
latency under load: 60000/427 = 140.52 ms
base RPM: 60000/16 = 3750 RPM
reduction RPM: 100-100*427/3750 = 88.6%
I understand apple's desire to have a single reported number with a single qualifier medium/high/... because in the end a link is only reliably usable if responsiveness under load stays acceptable, but with two numbers it is easier to see what one's ISP could do to help. (I guess some ISPs might already be unhappy with the single number, so this needs some diplomacy/tact)
Regards
Sebastian
*) Seemingly as quite some ISPs operate their own speedtest servers in their network and ignore customers not reaching the contracted rates into speedtest-servers located in different ASs. As the product is called internet access I a inclined to expect that my ISP maintains sufficient peering/transit capacity to reach the next tier of AS at my contracted rate (the EU legislative seems to agree, see EU directive 2015/2120).
**) Most do by creating load themselves and measuring throughput at the same time, bounceback IIUC will focus on the latency measurement and leave the load generation optional (so offers a mode to measure responsiveness of a live network with minimal measurement traffic). @Bob, please correct me if this is wrong.
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<pre class="moz-quote-pre" wrap="">
On Fri, Oct 21, 2022, 5:20 PM Dave Taht <a class="moz-txt-link-rfc2396E" href="mailto:dave.taht@gmail.com"><dave.taht@gmail.com></a> wrote:
One of the best talks I've ever seen on how to measure customer
satisfaction properly just went up after the P99 Conference.
It's called Misery Metrics.
After going through a deep dive as to why and how we think and act on
percentiles, bins, and other statistical methods as to how we use the
web and internet are *so wrong* (well worth watching and thinking
about if you are relying on or creating network metrics today), it
then points to the real metrics that matter to users and the ultimate
success of an internet business: Timeouts, retries, misses, failed
queries, angry phone calls, abandoned shopping carts and loss of
engagement.
<a class="moz-txt-link-freetext" href="https://www.p99conf.io/session/misery-metrics-consequences/">https://www.p99conf.io/session/misery-metrics-consequences/</a>
The ending advice was - don't aim to make a specific percentile
acceptable, aim for an acceptable % of misery.
I enjoyed the p99 conference more than any conference I've attended in years.
--
This song goes out to all the folk that thought Stadia would work:
<a class="moz-txt-link-freetext" href="https://www.linkedin.com/posts/dtaht_the-mushroom-song-activity-6981366665607352320-FXtz">https://www.linkedin.com/posts/dtaht_the-mushroom-song-activity-6981366665607352320-FXtz</a>
Dave Täht CEO, TekLibre, LLC
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<pre class="moz-signature" cols="72">--
David Collier-Brown, | Always do right. This will gratify
System Programmer and Author | some people and astonish the rest
<a class="moz-txt-link-abbreviated" href="mailto:dave.collier-brown@indexexchange.com">dave.collier-brown@indexexchange.com</a> | -- Mark Twain</pre>
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