The Algorithms That Make Google Maps Work

Hello, everyone! Isn't it true that we all utilise apps to obtain numerous services on a daily basis? But have you ever considered the algorithm that it employs? Today, we'll take a look at Google Maps, one of the most widely used services, and learn about the algorithm that powers it.

What exactly is Google Maps?

Google Maps, which has over a billion monthly active users, was created in 2005 as a desktop solution to help people go from " point A to point B ". It's been a long journey, and after more than 15 years, Maps has evolved into an indispensable service that we all use on a daily basis.

C++, JavaScript, XML, and Ajax are the languages utilised to create the Google Maps framework. We all have this app pre-installed on our Android phones, thanks to the original desktop solution. Now that we've covered the Maps, let's move on to the technical aspects of the programme.

What algorithm are they employing?

To compute the shortest distance from point A (Source) to point B, Google Maps employs two graph algorithms: Dijkstra's algorithm and A* algorithm (destination). A graph data structure is essentially a collection of nodes with edges and vertices defining them.

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The Algorithm of Dijkstra’s

If you've been programming for a long, you've most likely heard of Dijkstra's algorithm. One of the greedy methods used to optimise and identify the shortest path between nodes in a graph is Dijkstra's algorithm. Dijkstra's algorithm is a useful algorithm proposed in 1956 by Edsger.W. Dijkstra and published three years later.

There are numerous variations of this algorithm. The original technique looked for the shortest distance between two nodes, whereas the version starts with a single node as the source and then searches for the shortest path to other nodes. And it's this principle that Google Maps uses to calculate and display the shortest path between two points. This algorithm, however, has one flaw. Because the number of nodes in Google Maps is nearly limitless or uncountable, this technique may fail as time and space complexity increases. That's where the A* algorithm comes in handy.

 

Algorithm A*

The A* graph algorithm is a graph traversal and path search technique designed specifically for weighted graphs. Because of its completeness, optimality, and efficiency, this approach is chosen. The A* method, like Dijkstra's, employs a heuristic function to find a better and more efficient path. Unlike Dijkstra's method, the A* algorithm concentrates solely on the target nodes and ignores all other nodes, making it more efficient. It also considers factors like as time, distance, and other factors when optimising and selecting the best nodes.

 

That was enlightening, wasn't it?

 

So that the next time you use Google Maps to get somewhere, you'll recall the app's algorithm and how this way was chosen as the most efficient for you.

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