Over the last weekend, I tried to figure out what kind of node progression distribution we can expect to see in AoC. I figured that patches of civilization would be surrounded by level 0 nodes. So, to test my theory I wrote a little script that would simulate the progression in a 10x10 hexagonal grid where different nodes progress randomly (if they can) and also get sieged (if possible) at some random point in time.
The visualization looks like this:

I think that kind of distribution looks pretty cool and allows for keeping all regions interesting and fresh as there are only a few of them developed at a time.
Note: Keep in mind that Nodes won't be strict hexagons, so some Nodes may have more adjacent nodes, other Nodes may have fewer, and/or may be stretched out longer. So the image only gives some rough estimation, not an actual or solid prediction. Also player behaviour won't be that random. It's more likely to have some large blobs of player activity forming the node progression (at least in the beginning)
What I found however is that sometimes when a metropolis gets destroyed a new metropolis pops up just an instant later and I started wondering whether that kind of stuff could happen in AoC as well.
So imagine this scenario: You are living in a level 5 node for some time now and your node can't progress because of that other metropolis near your node. When the siege is declared against that metropolis you are added to the defenders of that node. But the people in your city actually have an interest in that metropolis getting destroyed, so instead of taking part in defending the metropolis, they start questing in their area, because they know: Once the metropolis is destroyed there will be only a short time frame to become the next metropolis in this region.
Is this a realistic scenario? Is there some cooldown for the next metropolis to show up? Do the players who participated in the siege (attacking or defending) get XP for the node they are citizens of or something similar? (Maybe this would be a cool question to answer in the next stream)
You can find my script
here. Feel free to play around with it and see how the node's distribution may evolve over long periods of time.