Here are some experiments on running the swapping algorithm with periodic
randomization of node positions. The idea is to study measures against
position clustering, and later on what can be made to counter attacks against
the swap algorithm. No attacks have been simulated yet, this is the pure
impact of randomizing positions on the swapping algorithm.

The network size was fixed to 10000 nodes, HTL to 100, and the average degree
was varied. Each run a network was initiated as the Kleinberg model, measured
by routing a while on it, and then positions were uniformly randomly assigned
between 0 and 1 before staring the swapping algorithm to recover the efficient
routing.

The major thing to study was the frequency of randomizing the position. One
run was evaluated for each different frequency X. Randomizing frequency X was
used as follows: each node randomizes its location each X'th swap that goes
out from that node. To avoid cyclic behaviour (at least of the simple case,
perhaps this needs to be extended) each nodes counter for doing this is
initialized independenty between 0 and X before starting the simulations.
Lets say a node randomly initalizes its counter to y (between 0 and X), then
it will randomize its location on the swap y,y+X,y+2X,y+3X... that starts
from it with a random walk (of length 6). This is an easy way to let a node
stay with a location for a while (unless swapping) and to let the neighbors
route through it before randomizing again. X=0 corresponds to not randomizing
at all.

Discussing the results:
There seems to be room for running a low-frequent randomization to begin with. 
For
one case (average degree=10) it even seems to perform better in some cases with 
randomization with a quite large period (this surely depends on that 
randomization
can help the algorithm get out of some suboptimal configurations). This does not
seem to happen for a larger average degree, perhaps because each randomization 
will
have impact on more links (but that is no controlled answer, just speculation at
the moment).

Another note: how quickly the algorithm improves the network from the entirely
randomized state is not of foremost interest here, the interesting thing is what
happens when the network is rather stable from swapping for a long period.
Therefore its the resulting level (on the right sides of the plots) that are
important, but the levels seem to have settled around some performance (I will
rerun the first simulation again to see how pure swapping without no 
randmization
behaves in a longer run)

Finally, we dont know if the observed behaviour here will be the same in the
current Freenet topology (since the efficiency of the swapping algorithm depends
on how much the topology deviates from the Kleinberg model in the first case).
Therefore any implementation attempt should be using defensively low periods of
randomization.

regards,
/Vilhelm
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