David L. Mills wrote:
> Richard,
>
> There were several different architecture computers considered in the
> 1995 and 1998 studies, incluing SPARC, Alpha, Intel and several lab
> instruments. All oscillators conformed to a simple model: white phase
> noise (slope -1) below the intercept, random-walk frequency noise (slope
> +0.5) above the intercept. This is equivalent to your model.
>
> Additional data are in the nanokernel documentation. The only
> differences are in the (x, y) intercept. You don't need das Buch to
> justify this model; there is evidence all over the place. Clocks of all
> kinds from cold rocks to Cesium oscillators all show very similar
> chacteristics, whether modelled in the time domain or frequency domain.
>
> It's easy to make your own Allan characteristic. Just let the computer
> clock free-run for a couple of weeks and record the offset relative to a
> known and stable standard, preferable at the smallest poll interval you
> can. The PPS from a GPS receiver is an ideal source, but you have to
> jerry-rig a means to capture each transition.
>
> Compute the RMS frequency differences, decimate and repeat. Don't take
> the following seriously, I lifted it without considering context, but
> that's the general idea. Be very careful about missing data, etc., as
> that creates spectral lines that mess up the plot.
>
> p = w; r = diff(x); q = y; i = 1; d = 1;
> while (length(q) >= 10)
> u = diff(p) / d;
> x2(i) = sqrt(mean(u .* u) / 2);
> u = diff(r) / d;
> x1(i) = sqrt(mean(u .* u) / 2);
> u = diff(q);
> y1(i) = sqrt(mean(u .* u) / 2);
> p = p(1:2:length(p));
> r = r(1:2:length(r));
> q = q(1:2:length(q));
> m1(i) = d; i = i + 1; d = d * 2;
> end
> loglog(m1, x2 * 1e6, m1, x1 * 1e6, m1, y1 * 1e6, m1, (x1 + y1) * 1e6)
> axis([1 1e5 1e-4 100]);
> xlabel('Time Interval (s)');
> ylabel('Allan Deviation (PPM)');
> print -dtiff allan
>
> Dave
>
> Richard B. Gilbert wrote:
>
>> Unruh wrote:
>>
>>> "David L. Mills" <[EMAIL PROTECTED]> writes:
>>>
>>>
>>>> David,
>>>
>>>
>>>
>>>
>>>> 1. I have explained in very gory detail in many places how the time
>>>> constant is chosen for the best accuracy using typical computer
>>>> oscillators and network paths. See the briefings on the NTP project
>>>> page and especially the discussion about the Allan intercept. If you
>>>> want the
>>>
>>>
>>>
>>>
>>> The Allan intercept is predicated on a very specific model of the
>>> noise in
>>> a clock ( as I recall basically random gaussian noise at high
>>> frequencies,
>>> and 1/f noise at low). It is not at all clear that real computers comply
>>> with that.
>>>
>>>
>>>> best accuracy over the long term, you had better respect that. Proof
>>>> positive is in my 1995 SIGCOMM paper, later IEEE Transactions on
>>>> Networking paper and das Buch. I abvsolutely relish scientific
>>>> critique, but see the briefings and read the papers first.
>>>
>>>
>>>
>>>
>>>> 2. To reduce the convergence time, reduce the time constant, but
>>>> only at the expense of long term accuracy. An extended treatise on
>>>> that is in das Buch, especially Chaptera 4, 6 and 12. I would be
>>>> delighted to hear critique of the material, but read the chapters
>>>> first.
>>>
>>>
>>>
>>>
>>> While you may know what in the world Das Buch is (Hitlers Mein
>>> Kampf?) I do
>>> not. Nor do I know where to get it.
>>
>>
>>
>> Computer Network Time Synchronization: The Network Time Protocol by
>> David L. Mills (Hardcover - Mar 24, 2006)
>>
>> Available from Amazon.com. You may be able to find a copy at a
>> University Book store. Be prepared for "Sticker Shock". It ain't
>> cheap! Publishing in small quantities is EXPENSIVE!!! It's different
>> when you can amortize your setup costs over 50,000 copies!
>>
>> "Das Buch" is unlikely to become a best seller!
>>
David,
Why are you telling me this? My contribution to this thread consisted
of the above exposition of the publication data and availability of "Das
Buch".
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