A node learns about the specialization of its
neighbors and vis versa. Will all of a node's
neighbors have about the same "opinion" of the node's
specailization?
The first answer I'll hear is "YES" of coarse. A well
integrated node will wind up being good at a
particular keyspace, and all its neighbors will know
this.
But wait, consider the fact that people aren't out
requesting random keys (though the search keys may
"look" random). Consider this senerio with 4 nodes
{A,B,C,D}.
Both A and B sepecialize in keyspace X. C and D
request from A and B. C tends to have requests for
freesites about cats, and likewise D gets them for
dogs.
It seems posible to have a network where C has learned
to get data from A and D from B. A has a cache full
of kitty pics and B has one full of doggy pics.
C would have reason to believe A is better than B in
keyspace X.
D would have reason to believe B is better than A in
keyspace X.
Therefore, how good A and B are in X is "subjective".
Ok, maybe someone has a good arguement why this type
of senerio is improbable. Does anyone have data to
suggest that something like this can/does happen? Is
there a way to gather this data? Perhaps I could
write some simple simulations based on the old code
from the freenet paper, where nodes have something
like "tastes".
My fear is that learning based on keys could be
sidetracked by learning based on "taste". While there
might be advantages like collecting together
"like-minded" nodes, my guess is that if something
like this does happen it might hurt the routing.
I hope my posts haven't been too pie in the sky
lately, I'd really like to help out with the routing;
it facinates (and frustrates) me.
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