Hi Neil,

On Jul 25, 2014, at 19:14 , Neil Davies <[email protected]> wrote:

> Try this thesis - Lucian used this for work at CERN, the description is in 
> there.... (see one of the appendicies) Analysis and predictive modeling of 
> the performance of the ATLAS TDAQ network

        Sweet, thanks a lot.

best regards
        sebastian

> 
> 
> On 25 Jul 2014, at 18:12, Sebastian Moeller <[email protected]> wrote:
> 
>> Hello Martin,
>> 
>> thanks a lot.
>> 
>> On Jul 25, 2014, at 18:32 , Martin Geddes <[email protected]> wrote:
>> 
>>> So what is ΔQ and how do you "compute" it (to the extent it is a "computed" 
>>> thing)?
>>> 
>>> Starting point: the only observable effect of a network is to lose and 
>>> delay data -- i.e. to "attenuate quality" by adding the toxic effects of 
>>> time to distributed computations. ΔQ is a morphism that relates the 
>>> "quality attenuation" that the network imposes to the application 
>>> performance, and describes the trading spaces at all intermediate layers of 
>>> abstraction. It is shown in the attached graphic.
>>> 
>>> Critically, it frames quality as something that can only be lost 
>>> ("attenuated"), both by the network and the application. Additionally, it 
>>> is stochastic, and works with random variables and distributions.
>>> 
>>> At its most concrete level, it is the individual impairment encountered by 
>>> every packet when the network in operation. But we don't want to have to 
>>> track every packet - 1:1 scale maps are pretty useless. So we need to 
>>> abstract that in order to create a model that has value.
>>> 
>>> Next abstraction: an improper random variable. This unifies loss and delay 
>>> into a single stochastic object.
>>> Next abstraction: received transport, which is a CDF where we are 
>>> interested in the properties of the "tail".
>>> 
>>> Next abstraction, that joins network performance and application QoE (as 
>>> relates to performance): relate the CDF to the application through a 
>>> Quality Transport Agreement. This "stochastic contract" is both necessary 
>>> and sufficient to deliver the application outcome.
>>> 
>>> Next concretisation towards QoE: offered load of demand, as a CDF.
>>> Next concretisation towards QoE: breach hazard metric, which abstracts the 
>>> application performance. Indicates the likelihood of the QTA contract being 
>>> broken, and how badly.
>>> Final concretisation: the individual application performance encountered by 
>>> every user. Again, a 1:1 map that isn't very helpful.
>>> 
>>> So as you can see, it's about as far away from a single point average 
>>> metric as you can possibly get. A far richer model is required in order to 
>>> achieve robust performance engineering.
>>> 
>>> It is "computed" using multi-point measurements to capture the 
>>> distribution. The G/S/V charts you see are based on processing that data to 
>>> account for various issues, including clock skew.
>>> 
>>> I hope that helps. We need to document more of this in public, which is an 
>>> ongoing process. 
>> 
>>      You lost me, I think what I should have asked for is a real example 
>> with numbers and the formulas ;) I guess that is deep in “secret sauce” 
>> territory. Alas, if that should be true it also means that deltaQ is not 
>> going to help me understand my network any better …
>> 
>> Best Regards
>>      Sebastian
>> 
>> 
>>> 
>>> Martin
>>> 
>>> On 25 July 2014 16:58, Sebastian Moeller <[email protected]> wrote:
>>> Hi Martin,
>>> 
>>> thanks for the pointers,
>>> 
>>> 
>>> On Jul 25, 2014, at 16:25 , Martin Geddes <[email protected]> wrote:
>>> 
>>> > You may find the following useful background reading on the state of the 
>>> > art in network measurement, and a primer on ΔQ (which is the property we 
>>> > wish to measure).
>>> >
>>> > First, start with this presentation: Network performance optimisation 
>>> > using high-fidelity measures
>>> > Then read this one to decompose ΔQ into G, S and V: Fundamentals of 
>>> > network performance engineering
>>> > Then read this one to get a bit more sense on what ΔQ is about: 
>>> > Introduction to ΔQ and Network Performance Science (extracts)
>>> >
>>> > Then read these essays:
>>> >
>>> > Foundation of Network Science
>>> > How to do network performance chemistry
>>> > How to X-ray a telecoms network
>>> > There is no quality in averages: IPX case study
>>> 
>>>         All of this makes intuitively sense, but it is a bit light on how 
>>> deltaQ is to be computed ;).
>>>         As far as I understand it also has not much bearing on my home 
>>> network; the only one under my control. Now, following the buffer bloat 
>>> discussion for some years, I have internalized the idea that bandwidth 
>>> alone does not suffice to describe the quality of my network connection. I 
>>> think that the latency increase under load (for unrelated flows) is the 
>>> best of all the bad single number measures of network dynamics/quality. I 
>>> should be related to what I understood deltaQ to depend on (as packet loss 
>>> for non real time flows will cause an increase in latency).  I think that 
>>> continuous measurements make a to n of sense for ISPs, backbone-operators, 
>>> mobile carriers … but at home, basically, I operate as my own network 
>>> quality monitor ;) (that is I try to pin point and debug (transient) 
>>> anomalies).
>>> 
>>> >
>>> > Martin
>>> >
>>> > For fresh thinking about telecoms sign up for my free newsletter or visit 
>>> > the Geddes Think Tank.
>>> > LinkedIn Twitter Mobile: +44 7957 499219 Skype: mgeddes
>>> > Martin Geddes Consulting Ltd, Incorporated in Scotland, number SC275827 
>>> > VAT Number: 859 5634 72 Registered office: 17-19 East London Street, 
>>> > Edinburgh, EH7 4BN
>>> >
>>> >
>>> >
>>> > On 25 July 2014 15:17, Sebastian Moeller <[email protected]> wrote:
>>> > Hi Neil,
>>> >
>>> >
>>> > On Jul 25, 2014, at 14:24 , Neil Davies <[email protected]> wrote:
>>> >
>>> > > Rich
>>> > >
>>> > > I have a deep worry over this style of single point measurement - and 
>>> > > hence speed - as an appropriate measure.
>>> >
>>> >         But how do you propose to measure the (bottleneck) link capacity 
>>> > then? It turns out for current CPE and CMTS/DSLAM equipment one typically 
>>> > can not relay on good QoE out of the box, since typically these devices 
>>> > do not use their (largish) buffers wisely. Instead the current remedy is 
>>> > to take back control over the bottleneck link by shaping the actually 
>>> > sent traffic to stay below the hardware link capacity thereby avoiding 
>>> > feeling the consequences of the over-buffering. But to do this is is 
>>> > quite helpful to get an educated guess what the bottleneck links capacity 
>>> > actually is. And for that purpose a speediest seems useful.
>>> >
>>> >
>>> > > We know, and have evidence, that throughput/utilisation is not a good 
>>> > > proxy for the network delivering suitable quality of experience. We 
>>> > > work with organisation (Telco’s, large system integrators etc) where we 
>>> > > spend a lot of time having to “undo” the consequences of “maximising 
>>> > > speed”. Just like there is more to life than work, there is more to QoE 
>>> > > than speed.
>>> > >
>>> > > For more specific comments see inline
>>> > >
>>> > > On 25 Jul 2014, at 13:09, Rich Brown <[email protected]> wrote:
>>> > >
>>> > >> Neil,
>>> > >>
>>> > >> Thanks for the note and the observations. My thoughts:
>>> > >>
>>> > >> 1) I note that speedof.me does seem to overstate the speed results. At 
>>> > >> my home, it reports 5.98mbps down, and 638kbps up, while 
>>> > >> betterspeedtest.sh shows 5.49/0.61 mbps. (speedtest.net gives numbers 
>>> > >> similar to the betterspeedtest.net script.)
>>> > >>
>>> > >> 2) I think we're in agreement about the peak upload rate that you 
>>> > >> point out is too high. Their measurement code runs in the browser. It 
>>> > >> seems likely that the browser pumps out a few big packets before 
>>> > >> getting flow control information, thus giving the impression that they 
>>> > >> can send at a higher rate. This comports with the obvious decay that 
>>> > >> ramps toward the long-term rate.
>>> > >
>>> > > I think that its simpler than that, it is measuring the rate at which 
>>> > > it can push packets out the interface - its real time rate is precisely 
>>> > > that - it can not be the rate being reported by the far end, it can 
>>> > > never exceed the limiting link. The long term average (if it is like 
>>> > > other speed testers we’ve had to look into) is being measured at the 
>>> > > TCP/IP SDU level by measuring the difference in time between the first 
>>> > > and last timestamps of data stream and dividing that into the total 
>>> > > data sent. Their “over-estimate” is because there are packets buffered 
>>> > > in the CPE that have left the machine but not arrived at the far end.
>>> >
>>> >         Testing from an openwrt router located at a 
>>> > high-symmetric-bandwidth location shows that speedof.me does not scale 
>>> > higher than ~ 130 Mbps server to client and ~15Mbps client to server (on 
>>> > the same connection I can get 130Mbps S2C and ~80Mbps C2S, so the 
>>> > asymmetry in the speedof.me results is not caused by my local 
>>> > environment).
>>> >         @Rich and Dave, this probably means that for the upper end of 
>>> > fiber and cable and VDSL connections speed of.me is not going to be a 
>>> > reliable speed measure… Side note www.sppedtest.net shows ~100Mbps S2C 
>>> > and ~100Mbps C2S, so might be better suited to high-upload links...
>>> >
>>> > >
>>> > >>
>>> > >> 3) But that long-term speed should be at or below the theoretical 
>>> > >> long-term rate, not above it.
>>> > >
>>> > > Agreed, but in this case knowing the sync rate already defines that 
>>> > > maximum.
>>> >
>>> >         I fully agree, but for ADSL the sync rate also contains a lot of 
>>> > encapsulation, so the maximum achievable TCP rate is at best ~90% of link 
>>> > rate. Note for cerowrt’s SQM system the link rate is exactly the right 
>>> > number to start out with at that system can take the encapsulation into 
>>> > account. But even then it is somewhat unintuitive to deduce the expected 
>>> > good-put from the link rate.
>>> >
>>> > >
>>> > >>
>>> > >> Two experiments for you to try:
>>> > >>
>>> > >> a) What does betterspeedtest.sh show? (It's in the latest CeroWrt, in 
>>> > >> /usr/lib/CeroWrtScripts, or get it from github: 
>>> > >> https://github.com/richb-hanover/CeroWrtScripts )
>>> > >>
>>> > >> b) What does www.speedtest.net show?
>>> > >>
>>> > >> I will add your question (about the inaccuracy) to the note that I 
>>> > >> want to send out to speedof.me this weekend. I will also ask that they 
>>> > >> include min/max latency measurements to their test, and an option to 
>>> > >> send for > 10 seconds to minimize any effect of PowerBoost…
>>> >
>>> >         I think they do already, at least for the download bandwidth; 
>>> > they start with 128Kb and keep doubling the file size until a file takes 
>>> > longer than 8 seconds to transfer, they only claim to report the numbers 
>>> > from that last transferred file, so worst case with a stable link and a 
>>> > bandwidth > 16kbps ;), it has taken at least 12 seconds (4 plus 8) of 
>>> > measuring before the end of the plot, so the bandwidth of at least the 
>>> > last half of the download plot should be representative even assuming 
>>> > power boost. Caveat, I assume that power boost will not be reset by the 
>>> > transient lack of data transfer between the differently sized files (but 
>>> > since it should involve the same IPs and port# why should power boost 
>>> > reset itself?).
>>> >
>>> > Best Regards
>>> >         Sebastian
>>> >
>>> >
>>> >
>>> > >>
>>> > >> Best regards,
>>> > >>
>>> > >> Rich
>>> > >>
>>> > >>
>>> > >>
>>> > >> On Jul 25, 2014, at 5:10 AM, Neil Davies <[email protected]> wrote:
>>> > >>
>>> > >>> Rich
>>> > >>>
>>> > >>> You may want to check how accurate they are to start.
>>> > >>>
>>> > >>> I just ran a “speed test” on my line (which I have complete control 
>>> > >>> and visibility over the various network elements) and it reports an 
>>> > >>> average “speed” (in the up direction) that is in excess of the 
>>> > >>> capacity of the line, it reports the maximum rate at nearly twice the 
>>> > >>> best possible rate of the ADSL connection.
>>> > >>>
>>> > >>> Doesn’t matter how pretty it is, if its not accurate it is of no use. 
>>> > >>> This is rather ironic as the web site claims it is the “smartest and 
>>> > >>> most accurate”!
>>> > >>>
>>> > >>> Neil
>>> > >>>
>>> > >>> <speedof_me_14-07-25.png>
>>> > >>>
>>> > >>> PS pretty clear to me what mistake they’ve made in the measurement 
>>> > >>> process - its to do with incorrect inference and hence missing the 
>>> > >>> buffering effects.
>>> > >>>
>>> > >>> On 20 Jul 2014, at 14:19, Rich Brown <[email protected]> wrote:
>>> > >>>
>>> > >>>> Doc Searls 
>>> > >>>> (http://blogs.law.harvard.edu/doc/2014/07/20/the-cliff-peronal-clouds-need-to-climb/)
>>> > >>>>  mentioned in passing that he uses a new speed test website. I 
>>> > >>>> checked it out, and it was very cool…
>>> > >>>>
>>> > >>>> www.speedof.me is an all-HTML5 website that seems to make accurate 
>>> > >>>> measurements of the up and download speeds of your internet 
>>> > >>>> connection. It’s also very attractive, and the real-time plots of 
>>> > >>>> the speed show interesting info. (screen shot at: 
>>> > >>>> http://richb-hanover.com/speedof-me/)
>>> > >>>>
>>> > >>>> Now if we could get them to a) allow longer/bigger tests to 
>>> > >>>> circumvent PowerBoost, and b) include a latency measurement so 
>>> > >>>> people could point out their bufferbloated equipment.
>>> > >>>>
>>> > >>>> I'm going to send them a note. Anything else I should add?
>>> > >>>>
>>> > >>>> Rich
>>> > >>>> _______________________________________________
>>> > >>>> Bloat mailing list
>>> > >>>> [email protected]
>>> > >>>> https://lists.bufferbloat.net/listinfo/bloat
>>> > >>>
>>> > >>
>>> > >
>>> > > _______________________________________________
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>>> 
>>> 
>>> <ΔQ morphism.png>
>> 
> 

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