It is used to solve real word problems like finding the best route to the destination location and the route for telecommunications and social networks. Users are considered a node in the Graph, and the wires are the edges connecting the users. If edges are represented as E and vertices are represented as V, then the graph G can be written as the set of vertices and edges, such as G (V, E)
Example:
Here’s a simple example of graph data structure:
It’s a simple undirected graph (one kind of Graph). Here the set of vertex is: {A, B, C,D,E,F}. Two vertices create an edge. For example, A and B are linked with an edge. However, A and F are not linked with any edges.
Graph Terminologies in Data Structure
The following are some important terms used in graph data structure:
Application of Graph Data Structure
A graph has many use cases. There are a lot of algorithms that use Graphs a lot. Here’re some of the applications of the Graph:
Google Maps uses graphs to find the intersection of two roads and calculate the distance between two locations. For example, Dijkstra, for finding the shortest distance between source and destination location. Facebook uses Graphs to find the mutual friend of the users. Its algorithm considers each user as a node of a graph. For resource allocation, DAG (Direct Acyclic Graph) is used. It checks the dependency of the resources. Google Search Engine uses graphs to create the ranking for websites. A mapping device uses the graph data structure. Router and t’s protocol uses the Graph to learn the path of the destination path.
