At random interval the node asks a random subset of the nodes in the rt for the estimator data they have of another node/subset of nodes (the two subsets can overlap). After that the node "merges" their results with its own estimator in a manner that would be as cancer-proof as possible in a network without trust. (that means removing outliers, averaging, etc.)
Drawbacks:
* increased network traffic. The timing will have to be chosen not to create a cascade effect.
* powerful attacker with many nodes totally screws up our estimates, or even worse - provides such data which would make the requesting node favor his cancer nodes.
Benefits:
* Nodes have a more consistent picture of each other's strengths and weaknesses.
* Newer nodes find their place faster
* The network does not become any more static
* Since topological neighbors know similar things about each other, each request from within the "neighborhood" will go directly to the best node.
"Neighborhood" is not rigidly defined; if a network map is drawn, there will be no rigid boundaries between shared estimator information; rather it will flow gradually, providing optimal routing paths. (ok this sounds psycho but its much easier to visualise than explain - will try and get a pic/graph soon)
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