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Re: Intradomain Traffic Engineering
From: Robert Boyle <robert () tellurian com>
Date: Wed, 18 Jan 2006 00:36:37 -0500
At 12:06 AM 1/18/2006, you wrote:
wrong prediction, the technique suffers very high MLU (as high as 140%).
Basically, I have the following two questions:
1. In the traces I have, there exist several intervals with a
huge, sudden increase of traffic on some links. The prediction
model I use cannot predict those 'big spikes'. Do these 'big
spikes' really happen in operational networks? Or are they merely
measurement errors? If they really happen, is there a gradual ramp
up of traffic in smaller time scale, say, on the order of tens of
seconds? Or do these 'big spikes' really occur very quickly, say,
in a few seconds?
Nobody can predict them so you build your network with excess
capacity from an overhead standpoint as well as a link standpoint.
Here are several reasons for variation and unpredictability. This is
not a comprehensive list and I'm sure others will add to it.
CNN or other major network coverage including major advertising
events - super bowl, victoria's secret show, etc. (10s of seconds)
SQL Slammer / Code Red / Nimda / or other major fast moving outbreaks
(10s of seconds - maybe. We saw the spread of SQL slammer within 2
seconds to many unmanaged colo customer machines)
depeering of any two or more large networks or routing mistakes or
flapping thus dampening (a few seconds to 10s of seconds to hours)
major provider outage which moves flows to other paths (a few seconds
to 10s of seconds)
fiber cuts / regional power outages (a few seconds to 10s of seconds)
significant events such as 9/11 & Katrina (a few seconds to many hours)
2. I have the option to make a tradeoff between average case
performance and worst case performance guarantee, but I don't know
which one is deemed more important by you. Are ISP networks
currently optimized for worst case or average case performance? Is
the trade-off between these two an appealing idea, or may the ISP
networks are already doing it?
Each ISP makes their own decisions based on their business needs,
budgets, and promised SLAs to customers
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