So let's do this.

Move Node Up

And so that's like making a small tree.

Because the nodes are filled in the tree from top to bottom and left to right, we can number them very naturally as follows.

Maybe I should ask you. So here's a skeleton to get you started.

I used numbers here, because it was really easy to do.

We're going to average it for the n nodes in the graph.

Then what's happening here is we have, how many nodes we have at that level?

So we give it a single source. We give it a single node in the network.

In the clustering coefficient of a graph, you have to sum all the nodes in the graph.

In the graph, we can talk about something called an Eulerian path.

Dijkstra is the name of the individual who first described and analyzed this algorithm for a single source shortest path.

If you take any 2 vertices, the set of hubs has to intersect, and the intersection mark contains a vertex on the shortest path between them.

It's configurable, but in our case, we're using a replication factor of 3, which means that if a piece of data lives on this node, it is also on this one and this one and that happens all around the ring.

And this has 2 neighbors 0, 0 and 1, 1 but both are already checked.

Then, for each pair of colors, we have to exclude that they are both true for every nodes.

What node 0 is is a dictionary of all the nodes that it is connected to directly.

We've got five nodes and five edges.

Node

Node

Node...

Nodes

Dodge

If we have some value in the heap and we know that the heap property is satisfied and what does that mean?

Here's a game tree for a stochastic 2 player game.

The shortestdistnode, you give it a mapping distances and it starts off with the best node undefined and best value something big from probably really want something bigger than this and for all the nodes that we have distances for

This isn't too hard we just make a note that degree centrality just means that degree which node has the highest degree.

We're going to again generate a graph on n nodes recursively. Same structure as before.

The way that it worked was each node of the network has a label.

So, like, Give me the money.

Otherwise, we recursively generate the two subgraphs.

We're going to make a link in the ring from node i to node i 1 mod n.

This algorithm captures a different notion of centrality.

I draw an extra node for x zero.

Node Name

DOM Node

DHT Nodes

Total Nodes

Node name

These formulas together define a unique schedule, which is the fastest possible schedule.

Once you know you can win the game or do the best you can, you don't need to find another way to do just as well.

let's talk about how we might implement them in Python.

Color of the nodes on DHT chart

And what is the maximum possible clustering coefficient for a node in B?

So starting from this node here, we can see this node can reach this one, and this one, well, and itself, and did we miss any?