Parallel breadth-first search

Imagine you are playing hide and seek with your friends in a big park. You want to search for your friends as quickly as possible, so you decide to split up and cover as much ground as possible. This is called parallel searching because you are all searching at the same time.

Now, let's say you decide to search the park using the "breadth-first" method. This means that you will start by searching the area closest to you, then move outwards to search further distances.

In order to parallelize this method, each of your friends will take a different section of the park to search. They will all start by searching the area closest to them, then move outwards in a circle to search further distances. This way, multiple friends can search different sections of the park at the same time, making the search faster.

Parallel breadth-first search is like this game of hide and seek. Instead of searching for friends in a park, we are searching for information or data in a computer system. By breaking up the search into smaller pieces and having multiple processes search at the same time, we can find the information we need much faster than if we tried to search it all at once.