Re: Mean vs Median

Hi Marius, Paul, and all who have contributed so far.

a quick reply/differing opinion below.

> -----Original Message-----
> From: bmwg [mailto:[email protected]] On Behalf Of Marius Georgescu
...
> > On Nov 10, 2015, at 02:40, Paul Emmerich <[email protected]>
> wrote:
> >
> > Hi,
> >
> > On 03.11.15 09:45, Stenio Fernandes wrote:
> >> a word of caution here... a number of phenomena in computer networks
> >> follows a heavy-tailed probability distribution function, which means
> >> that there is a non-negligible probability that a random variable
> >> will take huge values. these values might be erroneously considered
> as outliers.
> >
> > this is a really important point. I have benchmarked software where
> the 99th percentile of the latency is twice the average/median and the
> 99.9th percentile ten times the average/median.
> 
> Can you give us more context (test setup; physical/virtualized
> tester/DUT; one tester/sender_receiver tester ... ) on these
> measurements?
[ACM] 
My understanding (and I've seen some results, but I've had trouble
re-locating them) is that both outliers and bimodal distributions
are more common in the world of virtual DUTs than they were in the
physical/past. Not only does this affect analysis, but the threshold
waiting time for packet arrival must be chosen carefully to even
measure such outliers.

> 
> > This is an important performance characteristic for latency-sensitive
> applications that isn't captured by taking just 20 measurements. So I'd
> really like to see a standard that calls for thousands of latency
> measurements to capture this properly.
> >
> 
> I think we should keep practicality in mind here. If we follow
> RFC2544.latency measurement, the frame stream has to be 2 min long. 2000
> min ~ 33h  of testing for just one test sounds unreasonable to me. I
> would agree to have a lower bound for the sample size as RFC2544
> actually recommends (n > 20).
[ACM] 
Latency (delay) and delay variation need many single delay measurements
to be meaningful. One way to view the variation is for a single flow of
packets with spacing that might come from an application, say 20ms spacing
for VoIP. Collecting a few thousand of such packets should not take so long.
 

> 
> > You can also get interesting insights into a black-box device by
> > looking at histograms/probability density functions. For example, you
> > can figure out if the device processes packets in batches, estimate
> > the batch size, figure out at which rates interrupt moderation
> > algorithms change etc. (This is, of course, not really a performance
> > metric, just an interesting insight.)
> >
> 
> I agree this is an interesting insight. It can also be the base for a
> decision between summarizing functions. However, in the light of
> consistency and simplicity of the methodology, I think we would need to
> recommend one function. We could do that depending on the metric/DUT
> characteristics, previous testing behavior …
[ACM] 
I agree the right summary statistics can only be chosen after an examination
of the raw distribution for a particular scenario.  If Bi-modal, the central
statistics of the sample could be meaningless. Without this examination,
I don't think one recommendation can always be right.

my 2 cents
Al
(as a participant)


> 
> >
> > Paul
> >
> > --
> > Paul Emmerich
> > Technical University of Munich (TUM)
> > Department of Informatics
> > Chair for Network Architectures and Services
> >
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