comments on draft-py-multi6-gapi-00.txt

[Kurt Erik Lindqvist <kurtis@kurtis.pp.se>]

I have gone through the above draft again and started thinking. 
Although the draft as such does not give any solution in itself to 
mulithoming it is part of other solutions. I am not convinced it scales 
though. I somehow have the feeling it is no different than the 
TLA/NLA/SLA model that was abandoned.

Mainly my concerns are that this is based on statistics. The draft says 
that the options that are available to base this on is geography or 
population. I would add Geopolicy and economics.

If we take Sweden or Switzerland as examples, these are countries with 
relatively small populations but with a high number of large 
multinationals per capita. Multinationals will have a higher burn rate 
of addresses, especially in multihoming than "ordinary" users will. 
With the GAPI addresses, instead large countries that might have a 
lower order of multihoming is gaining advantage.

You can also argue that address consumption will most likely NOT follow 
geographic boundaries. If I take Stockholm, Ericsson for example have 
their HQ in a relatively unpopulated area. Also the "swedish silicon 
valley" have a high number of multinationals that will want to 
mulithome, but relatively small population.

The more I think on this, the more I think that any model that tries to 
align address usage / availability to Geopolitics, economics, address 
usage, etc - will not scale. We will end up just adding more and more 
allocation blocks and the situation will be similar to todays.

- kurtis -