[e2e] RTO Estimation... was "Agility..."

[Sireen Habib Malik]

Hi all,

I have been thinking about David's emails and some points raised by 
Detlef in the background discussion. It's a learning process.

So ...there are some questions which I think are important in the 
context of this discussion.

We say that the RTT's distribution is heavy-tailed. However, the 
discussion on heavy-tailed sized files, the resultant LRD in the traffic 
and the sub-exponential queue occupancy distribution, is based upon  the 
"open-loop" queue anaylsis.

However, TCP is a "closed-loop" protocol (David's point).

The first set of questions then is, "what impacts the queue occupancy 
distribution more, the closed loop operation, or the heavy-tailedness of 
E2E distribution?", or, "under what loads/traffic conditions one of them 
is more dominant?" , or, "is there a dependency between them?".

Second point: It is clear that present RTO estimation will work in the 
frame of assumptions under which it is supposed to work. Like Detlef 
says, "nobody will complain that a car does not run if it is out of 
gas", so nobody should complain if RTO estimator does not work when 
traffic parameters do not fall inside the space of the relevant assumptions.

If that is true then one way to resolve this issue is to adjust/shape 
traffic in such a way that RTO should work (I think this is what Detlef 
is saying), or make a "general purpose" RTO estimator that 
reduces/relaxes the set of assumptions - ideally, it should work if IID 
assumption holds, or not.

I think the work in the second direction is more general, and conducive 
to practical environments. How difficult or easy it is, I don't know! A 
good way is to first find out, if there is any work already done in this 
direction?


Thanks and regards,
Sireen Malik















Christian Huitema wrote:

>I think we should just look at a simple question. Does the current
>algorithm actually works? 
>
>I personally did measurements 6 years ago. The measurement of
>tcp-connect times to various web servers clearly showed a power law
>distribution. There is in fact a history of finding power laws in
>measurement of communication systems. In fact, Mandelbrot work on
>fractals started with an analysis of the distribution of errors on a
>modem link! Based on all that, it is quite reasonable to assume that the
>distribution of RTT measurement follows a power law. 
>
>People will immediately mention that it should be a truncated power law,
>but even that is far from clear. There is at least anecdotal evidence of
>packets being held up in queues and then transmitted after a very long
>time, e.g. half an hour...
>
>The current RTT estimators are based on exponential averages of
>consecutive samples of delays and variations. This is an issue, as the
>exponential average of a heavy tailed distribution also is a heavy
>tailed distribution. If you plug that in a simulation, you will observe
>that the estimates behave erratically. 
>
>My personal feeling is that the current RTT estimators do not actually
>work.
>
>-- Christian Huitema
>  
>


-- 
M.Sc.-Ing. Sireen Malik

Communication Networks
Hamburg University of  Technology
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