Subject: [aqm] chrome web page benchmarker fixed

From: Dave Taht <[email-masked]>
Date: Thu, 17 Apr 2014 10:49:13 -0700

Getting a grip on real web page load time behavior in an age of
sharded websites,
dozens of dns lookups, javascript, and fairly random behavior in ad services
and cdns against how a modern browsers behaves is very, very hard.

it turns out if you run

google-chrome --enable-benchmarking --enable-net-benchmarking

(Mac users have to embed these options in their startup script - see
 http://www.chromium.org/developers/how-tos/run-chromium-with-flags )

enable developer options and install and run the chrome web page benchmarker,
( https://chrome.google.com/webstore/detail/page-benchmarker/channimfdomahekjcahlbpccbgaopjll?hl=en
)

that it works (at least for me, on a brief test of the latest chrome, on linux.
Can someone try windows and mac?)

You can then feed in a list of urls to test against, and post process
the resulting .csv file to your hearts content. We used to use this
benchmark a lot while trying to characterise typical web behaviors
under aqm and packet scheduling systems under load. Running
it simultaneously with a rrul test or one of the simpler tcp upload or download
tests in the rrul suite was often quite interesting.

It turned out the doc has been wrong a while as to the name of the second
command lnie option. I was gearing up mentally for having to look at
the source....

http://code.google.com/p/chromium/issues/detail?id=338705

/me happy

-- 
Dave Täht

Heartbleed POC on wifi campus networks with EAP auth:
http://www.eduroam.edu.au/advisory.html

---

From: William Chan (陈智昌) <[email-masked]>
Date: Thu, 17 Apr 2014 12:01:46 -0700

Speaking as the primary Chromium developer in charge of this relevant code,
I would like to caution putting too much trust in the numbers generated.
Any statistical claims about the numbers are probably unreasonable to make.

Reasons:
* We don't actively maintain this code. It's behind the command line flags.
They are broken. The fact that it still results in numbers on the benchmark
extension is an example of where unmaintained code doesn't have the UI
disabled, even though the internal workings of the code fail to guarantee
correct operation. We haven't disabled it because, well, it's unmaintained.
* We don't make sure to flush all the network state in between runs, so if
you're using that option, don't trust it to work.
* If you have an advanced Chromium setup, this definitely does not work. I
advise using the benchmark extension only with a separate Chromium profile
for testing purposes. Our flushing of sockets, caches, etc does not
actually work correctly when you use the Chromium multiprofile feature and
also fails to flush lots of our other network caches.
* No one on Chromium really believes the time to paint numbers that we
output :) It's complicated. Our graphics stack is complicated. The time
from when Blink thinks it painted to when the GPU actually blits to the
screen cannot currently be corroborated with any high degree of accuracy
from within our code.
* It has not been maintained since 2010. It is quite likely there are many
other subtle inaccuracies here.

In short, while you can expect it to give you a very high level
understanding of performance issues, I advise against placing non-trivial
confidence in the accuracy of the numbers generated by the benchmark
extension. The fact that numbers are produced by the extension should not
be treated as evidence that the extension actually functions correctly.

Cheers.

On Thu, Apr 17, 2014 at 10:49 AM, Dave Taht <[email-masked]> wrote:

> (
> https://chrome.google.com/webstore/detail/page-benchmarker/channimfdomahekjcahlbpccbgaopjll?hl=en
> )
>
> _______________________________________________
> aqm mailing list
> [email-masked]
> https://www.ietf.org/mailman/listinfo/aqm
>

---

From: Dave Taht <[email-masked]>
Date: Thu, 17 Apr 2014 14:07:27 -0700

On Thu, Apr 17, 2014 at 12:01 PM, William Chan (陈智昌)
<[email-masked]> wrote:
> I would like to caution putting too much trust in the numbers generated. Any
> statistical claims about the numbers are probably unreasonable to make.

Sigh. Other benchmarks such as the apache ("ab") benchmark
are primarily designed as stress testers for web servers, not as realistic
traffic. Modern web traffic has such a high level of dynamicism in it,
that static web page loads along any distribution, seem insufficient,
passive analysis of aggregated traffic "feels" incorrect relative to the
sorts of home and small business traffic I've seen, and so on.

Famous papers, such as this one:

http://ccr.sigcomm.org/archive/1995/jan95/ccr-9501-leland.pdf

Seem possibly irrelevant to draw conclusions from given the kind
of data they analysed and proceeding from an incorrect model or
gut feel for how the network behaves today seems to be foolish.

Even the most basic of tools, such as httping, had three basic bugs
that I found in a few minutes of trying to come up with some basic
behaviors yesterday:

https://lists.bufferbloat.net/pipermail/bloat/2014-April/001890.html

Those are going to be a lot easier to fix than diving into the chromium
codebase!

There are very few tools worth trusting, and I am always dubious
of papers that publish results with unavailable tools and data. The only
tools I have any faith in for network analysis are netperf, netperf-wrapper,
tcpdump and xplot.org, and to a large extent wireshark. Toke and I have
been tearing apart d-itg and I hope to one day be able to add that to
my trustable list... but better tools are needed!

Tools that I don't have a lot of faith in include that, iperf, anything written
in java or other high level languages, speedtest.net, and things like
shaperprobe.

Have very little faith in ns2, slightly more in ns3, and I've been meaning
to look over the mininet and other simulators whenever I got some spare
time; the mininet results stanford gets seem pretty reasonable and I
adore their reproducing results effort. Haven't explored ndt, keep meaning
to...

> correct operation. We haven't disabled it because, well, it's unmaintained.

As I mentioned I was gearing up for a hacking run...

The vast majority of results I look at are actually obtained via
looking at packet captures. I mostly use benchmarks as abstractions
to see if they make some sense relative to the captures and tend
to compare different benchmarks against each other.

I realize others don't go into that level of detail, so you have given
fair warning! In our case we used the web page benchmarker as
a means to try and rapidly acquire some typical distributions of
get and tcp stream requests from things like the alexa top 1000,
and as a way to A/B different aqm/packet scheduling setups.

... but the only easily publishable results were from the benchmark itself,
and we (reluctantly) only published one graph from all the work that
went into it 2+ years back and used it as a test driver for the famous
ietf video, comparing two identical boxes running it at the same time
under different network conditions:

https://www.bufferbloat.net/projects/cerowrt/wiki/Bloat-videos#IETF-demo-side-by-side-of-a-normal-cable-modem-vs-fq_codel

from what I fiddled with today, it is at least still useful for that?

moving on...

The web model in the cablelabs work doesn't look much like my captures,
in addition to not modeling dns at all, and using a smaller IW than google
it looks like this:

>> Model single user web page download as follows:

>> - Web page modeled as single HTML page + 100 objects spread evenly
>> across 4 servers. Web object sizes are currently fixed at 25 kB each,
>> whereas the initial HTML page is 100 kB. Appendix A provides an
>> alternative page model that may be explored in future work.

Where what I see is a huge number of stuff that fits into a single
iw10 slow start episode and some level of pipelining on larger stuff, so that a
large number of object sizes of less than 7k with a lightly tailed distribution
outside of that makes more sense.

(I'm not staring at appendix A right now, I'm under the impression
 it was better)

I certainly would like more suggestions for models and types
of web traffic, as well as simulation of https + pfs traffic,
spdy, quic, etc....

>> - Server RTTs set as follows (20 ms, 30 ms, 50 ms, 100 ms).

Server RTTs from my own web history tend to be lower than 50ms.

>> - Initial HTTP GET to retrieve a moderately sized object (100 kB HTML
>> page) from server 1.

An initial GET to google fits into iw10 - it's about 7k.

>> - Once initial HTTP GET completes, initiate 24 simultaneous HTTP GETs
>> (via separate TCP connections), 6 connections each to 4 different
>> server nodes

I usually don't see more than 15. and certainly not 25k sized objects.

 > - Once each individual HTTP GET completes, initiate a subsequent GET
> to the same server, until 25 objects have been retrieved from each
> server.

> you're using that option, don't trust it to work.

The typical scenario we used was a run against dozens or hundreds of urls,
capturing traffic, while varying network conditions.

Regarded the first run as the most interesting.

Can exit the browser and restart after a run like that.

At moment, merely plan to use the tool primarily to survey various
web sites and load times while doing packet captures. Hope was
to get valid data from the network portion of the load, tho...

> for testing purposes. Our flushing of sockets, caches, etc does not actually
> work correctly when you use the Chromium multiprofile feature and also fails
> to flush lots of our other network caches.

noted.

> output :) It's complicated. Our graphics stack is complicated. The time from

I actually care only about time-to-full layout as that's a core network
effect...

> when Blink thinks it painted to when the GPU actually blits to the screen
> cannot currently be corroborated with any high degree of accuracy from
> within our code.

> other subtle inaccuracies here.

Grok.

> extension. The fact that numbers are produced by the extension should not be
> treated as evidence that the extension actually functions correctly.

OK, noted. Still delighted to be able to have a simple load generator
that exercises the browsers and generates some results, however
dubious.

-- 
Dave Täht

NSFW: https://w2.eff.org/Censorship/Internet_censorship_bills/russell_0296_indecent.article

---

From: William Chan (陈智昌) <[email-masked]>
Date: Thu, 17 Apr 2014 15:29:45 -0700

I understand the desire for this code to work, and if I had more bandwidth,
I would definitely fix it sooner. For now, all I can say is, be aware of
the potential issues with the code and use at your own risk. Sorry that we
don't have more bandwidth now to get this working sooner.

On Thu, Apr 17, 2014 at 2:07 PM, Dave Taht <[email-masked]> wrote:

> Any
> actually
> from
> NSFW:
> https://w2.eff.org/Censorship/Internet_censorship_bills/russell_0296_indecent.article
>

---

From: Greg White <[email-masked]>
Date: Fri, 18 Apr 2014 18:15:27 +0000

Dave, 

We used the 25k object size for a short time back in 2012 until we had
resources to build a more advanced model (appendix A).  I did a bunch of
captures of real web pages back in 2011 and compared the object size
statistics to models that I'd seen published.  Lognormal didn't seem to be
*exactly* right, but it wasn't a bad fit to what I saw.  I've attached a
CDF.

The choice of 4 servers was based somewhat on logistics, and also on a
finding that across our data set, the average web page retrieved 81% of
its resources from the top 4 servers.  Increasing to 5 servers only
increased that percentage to 84%.

The choice of RTTs also came from the web traffic captures. I saw
RTTmin=16ms, RTTmean=53.8ms, RTTmax=134ms.

Much of this can be found in
https://tools.ietf.org/html/draft-white-httpbis-spdy-analysis-00

In many of the cases that we've simulated, the packet drop probability is
less than 1% for DNS packets.  In our web model, there are a total of 4
servers, so 4 DNS lookups assuming none of the addresses are cached. If
PLR = 1%, there would be a 3.9% chance of losing one or more DNS packets
(with a resulting ~5 second additional delay on load time).  I've probably
oversimplified this, but Kathie N. and I made the call that it would be
significantly easier to just do this math than to build a dns
implementation in ns2.  We've open sourced the web model (it's on Kathie's
web page and will be part of ns2.36) with an encouragement to the
community to improve on it.  If you'd like to port it to ns3 and add a dns
model, that would be fantastic.

-Greg

On 4/17/14, 3:07 PM, "Dave Taht" <[email-masked]> wrote:

>https://www.bufferbloat.net/projects/cerowrt/wiki/Bloat-videos#IETF-demo-s
>ide-by-side-of-a-normal-cable-modem-vs-fq_codel
>
>>> that it works (at least for me, on a brief test of the latest chrome,
>>>on
>>> linux.

---

From: [email-masked]
Date: Fri, 18 Apr 2014 14:48:08 -0400 (EDT)

Why is the DNS PLR so high?  1% is pretty depressing.
 
Also, it seems odd to eliminate 19% of the content retrieval because the tail is fat and long rather than short.  Wouldn't it be better to have 1000 servers?

On Friday, April 18, 2014 2:15pm, "Greg White" <[email-masked]> said:

> >>> it simultaneously with a rrul test or one of the simpler tcp upload
> or
> >>> download
> Cerowrt-devel mailing list
> [email-masked]
> https://lists.bufferbloat.net/listinfo/cerowrt-devel
>

---

From: Dave Taht <[email-masked]>
Date: Fri, 18 Apr 2014 12:05:15 -0700

> *exactly* right, but it wasn't a bad fit to what I saw.  I've attached a

That does seem a bit large on the initial 20%.

Hmm.

There is a second kind of major case, where you are
moving around on the same web property, and hopefully many
core portions of the web page(s) such as the css and javascript,
basic logos and other images, are cached. Caching is handled
two ways, one is to explicitly mark the data as cacheable for
a certain period, the other is an if-modified-since request,
which costs RTTs for setup and the query. I am
under the impression that we generally see a lot more of the
latter than the former these days.

> RTTmin=16ms, RTTmean=53.8ms, RTTmax=134ms.

Get a median?

My own stats are probably quite skewed lower from being in california,
and doing some tests from places like isc.org in redwood city, which
is insanely well
co-located.

> https://tools.ietf.org/html/draft-white-httpbis-spdy-analysis-00

Thx!

> less than 1% for DNS packets.  In our web model, there are a total of 4

I think we have the ability to get a better number for dns loss now.

> implementation in ns2.

The specific thing I've been concerned about was not the probability of
a dns loss, although as you note the consequences are huge -
but the frequency and cost of a cache miss and the resulting fill.

This is a very simple namebench test against the alexa top 1000:

http://snapon.lab.bufferbloat.net/~d/namebench/namebench_2014-03-20_1255.html

This is a more comprehensive one taken against my own recent web history file.

http://snapon.lab.bufferbloat.net/~d/namebench/namebench_2014-03-24_1541.html

Both of these were taken against the default SQM system in cerowrt
against a cable modem, so you can
pretty safely assume the ~20ms (middle) knee in the curve is basically
based on physical
RTT to the nearest upstream DNS server.

And it's a benchmark so I don't generally believe in the relative hit
ratios vs a vs "normal traffic", but do think the baseline RTT, and
the knees in the curves in the cost of a miss and file are relevant.

(it's also not clear to me if all cable modems run a local dns server)

Recently simon kelly added support for gathering hit and miss
statistics to dnsmasq 2.69.

They can be obtained via  a simple dns lookup as answers to queries of
class CHAOS and type TXT in domain bind. The domain names are
cachesize.bind, insertions.bind, evictions.bind, misses.bind,
hits.bind, auth.bind and servers.bind. An example command to query
this, using the dig utility would be

dig +short chaos txt cachesize.bind

It would be very interesting to see the differences between dnsmasq
without DNSSEC, with DNSSEC and with DNSSEC and
--dnssec-check-unsigned (checking for proof of non-existence) - we've
been a bit concerned about the overheads of the last in particular.

Getting more elaborate stats (hit, miss, and fill costs) is under discussion.

> We've open sourced the web model (it's on Kathie's

As part of the google summer of code I am signed up to mentor a
student with tom for the *codel related bits
in ns3, and certainly plan to get fingers dirty in the cablelabs drop,
and there was a very encouraging patch set distributed around for
tcp-cubic with hystart support recently as well as a halfway decent
802.11 mac emulation.

As usual, I have no funding, personally, to tackle the job, but I'll
do what I can anyway. It would be wonderful to finally have all the
ns2 and ns3 code mainlined for more people to use it.

-- 
Dave Täht

---

From: Greg White <[email-masked]>
Date: Fri, 18 Apr 2014 19:27:44 +0000

In most cases it was *far* less than 1%.  In our DOCSIS 3.1 scenarios it is more like 1e-5 to 1e-4 (1e-3 worst case for the bufferbloated drop tail baseline) which means that implementing dns in the model would have affected on the order of 1 out of every 2500 page loads.

As with any model of reality, there is a tradeoff between complexity and fidelity, right? We chose 4 servers as being a reasonable and practical number.  Many of the most popular sites actually don't distribute content that widely (e.g. Google only used 3 servers in our measurements), and the worst case was 32 servers.   In reality every web page is different, and you could come up with an arbitrarily complex model and it still wouldn't match some version of reality.  In my view, we want to have something that is practical to implement and close enough to reality to be useful.  In the AQM-evaluation draft currently, the model is a single 700kB file served from a single server.

Greg

From: "[email-masked]<mailto:[email-masked]>" <[email-masked]<mailto:[email-masked]>>
Date: Friday, April 18, 2014 at 12:48 PM
To: Greg White <[email-masked]<mailto:[email-masked]>>
Cc: Dave Taht <[email-masked]<mailto:[email-masked]>>, "William Chan (陈智昌)" <[email-masked]<mailto:[email-masked]>>, "[email-masked]<mailto:[email-masked]>" <[email-masked]<mailto:[email-masked]>>, "[email-masked]<mailto:[email-masked]>" <[email-masked]<mailto:[email-masked]>>, bloat <[email-masked]<mailto:[email-masked]>>
Subject: Re: [Cerowrt-devel] [aqm] chrome web page benchmarker fixed

On Friday, April 18, 2014 2:15pm, "Greg White" <[email-masked]<mailto:[email-masked]>> said:

> On 4/17/14, 3:07 PM, "Dave Taht" <[email-masked]<mailto:[email-masked]>> wrote:
>
> ><[email-masked]<mailto:[email-masked]>> wrote:
> >> On Thu, Apr 17, 2014 at 10:49 AM, Dave Taht <[email-masked]<mailto:[email-masked]>>
> wrote:
> >>>
> >>> [email-masked]<mailto:[email-masked]>
> >[email-masked]<mailto:[email-masked]>
> [email-masked]<mailto:[email-masked]>

---

From: Dave Taht <[email-masked]>
Date: Fri, 18 Apr 2014 12:40:52 -0700

> the knees in the curves in the cost of a miss and file are relevant.

To be utterly clear here, the ~20ms knee in this data is a variable dependent
on the RTT to the nearest upstream DNS server. Most - nearly all -
ISPs - have a hefty dns server in their co-location facility, but the
baseline physical RTT is dependent on the actual technology in use.

The actual RTT of an query is dependent on the outstanding queue
length in a single queue AQM, unless otherwise prioritized. If prioritized
(cerowrt's 3 band system does this for queries coming from the router)
I imagine the packet loss rate drops hugely, also.

To give an extreme example of the DNS rtt problem, dns lookups over
satellite links take
800+ms, and this is one reason why web proxy servers are so common
in such environments as the whole query is shipped to a local-to-the-internet
proxy server so as to avoid this rtt cost. This technique is of increasingly
limited value in an age of e2e encryption.

Also: recently we've seen increasing use of non-local or otherwise redirected
dns servers such as here

http://www.cnet.com/news/google-confirms-turkey-is-blocking-its-dns-service/

It would be a good research project for someone to catagorize typical
nearest-upstream DNS RTTs, the availability of local-to-site dns
servers, hit/miss ratios
in homes and small business, the cost of dnssec, etc.

-- 
Dave Täht

---

From: Greg White <[email-masked]>
Date: Fri, 18 Apr 2014 20:41:03 +0000

>> RTTmin=16ms, RTTmean=53.8ms, RTTmax=134ms.

Median value was 62ms.

>and doing some tests from places like isc.org in redwood city, which

Mine are probably skewed too. I was told that global median (at the time I
collected this data) was around 100ms.

---

From: Dave Taht <[email-masked]>
Date: Sat, 19 Apr 2014 12:29:05 -0700

> collected this data) was around 100ms.

Well, the future is already here, just not evenly distributed. Nearly every
sample I'd taken at the same time as from, almost entirely from major
cities, came in at under 70ms median.

It strikes me that a possibly useful metric would be object size vs RTT,
over time.

-- 
Dave Täht

---

From: Dave Taht <[email-masked]>
Date: Wed, 30 Apr 2014 07:09:33 -0700

Doug Orr recommended to us that we give

http://www.chromium.org/developers/telemetry

a shot in generating reproducible web traffic models.