[e2e] Delivery times in mobile networs? Re: Are there any persons interested in TCP over mobile wireless networks in Germany?

[Detlef Bosau]

Am 12.12.2012 23:36, schrieb Lachlan Andrew:
> Greetings Detlef,
>
> Of course you can use an EWMA filter to estimate a non-stationary
> process.  Why do you think you couldn't?

You should use 15.

It's just simpler to implement.

(For the rest, I recommend looking it up in a textbook on mathematical 
statistics. You cannot estimate parameters, which simply don't exist.
Unfortunately, a C-compiler does only syntax checking on programs, hence 
it cannot prevent semantic nonsense.)

>
> In a non-stationary process, such as fading, there is usually
> considerable temporal correlation.

EWMA filters are estimators for a random variable's expectation.

And, like other ARMA filters as well, this makes sense in a series of 
i.i.d. random variables.

>    If the time constant of the filter
> is short compared with the "body" of the autocorrelation of the
> delivery times, then the non-stationarity makes essentially no
> difference.

In that case, we may talk aboult "nearly stationary" processes.



> If you want to be taken seriously (as I know you do) then it would be
> wise to tone down your criticism of other people's work.  Although it

Lachlan, it's not a matter of tone.

If you think about TCP's RTO, this is a confidence interval estimated 
from observations of successful deliveries.
Simply think of some mobile access network with a sudden link outage.

What does an RTO mean in that case?

What I point to, is written in Edge's original paper from 1983 or 1984. 
So, I wonder why you are that surprised when I repeat something, which 
is accepted in CS for nearly 30 years now.

I don't see "criticism" when I point to accepted knowledge and point to 
errors.

And EWMA filters, like other ARMA estimators, simply cannot applied to 
time series when the necessary assumptions and conditions are not met.

When someone tells me 5+5 were 11, this is not a matter of tone, this is 
simply wrong.


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