A directed graph, also known as a digraph, is a type of data structure that represents a collection of vertices or nodes connected by directed edges. In a directed graph, each edge has an orientation or direction associated with it. This means that the relationship between two nodes is asymmetrical and can only be traversed in one direction.
Structure of a Directed Graph
In a directed graph, the vertices are represented by circles or dots, and the edges are represented by arrows pointing from one vertex to another. The arrow indicates the direction of the edge, showing which vertex is the source and which vertex is the destination.
Example:
Consider a simple directed graph with three vertices A, B, and C. The edges connecting these vertices are as follows:
– Edge from A to B
– Edge from B to C
– Edge from C to A
This can be visualized as follows:
Diagram:
Properties of Directed Graphs
Directed graphs have several important properties that distinguish them from undirected graphs:
1. Directionality: As mentioned earlier, every edge in a directed graph has an associated direction. This allows for oneway relationships between nodes.
2. Cyclic or Acyclic: A directed graph may contain cycles, where a node can be reached from itself through multiple edges. On the other hand, an acyclic directed graph does not contain any cycles.
3. InDegree and OutDegree: Indegree refers to the number of incoming edges to a node, while outdegree refers to the number of outgoing edges from a node.
4. Connectivity: In a strongly connected directed graph, there exists a directed path between every pair of vertices. In contrast, a weakly connected directed graph may have disconnected components.
Let’s analyze the directed graph mentioned earlier:
– Vertex A has an outdegree of 1 and an indegree of 1.
– Vertex B has an outdegree of 1 and an indegree of 1.
– Vertex C has an outdegree of 1 and an indegree of 1.
This graph is both cyclic and strongly connected since there is a path from every vertex to every other vertex.
Applications of Directed Graphs
Directed graphs find applications in various fields, including computer science, social networks, transportation systems, and more. Some common uses are:
– Routing Algorithms: Directed graphs are used to represent network topologies and find the shortest paths between nodes using algorithms like Dijkstra’s algorithm or BellmanFord algorithm.
– Dependency Analysis: Directed graphs help identify dependencies between tasks or modules in software development, enabling efficient scheduling or build systems.
– Web Page Ranking: Search engine algorithms such as Google’s PageRank utilize directed graphs to analyze the link structure of websites and determine their relevance.

Dijkstra’s Algorithm:

BellmanFord Algorithm:
Dijkstra’s algorithm is a popular algorithm for finding the shortest path between two nodes in a graph. It can be applied to both directed and undirected graphs but is commonly used with weighted edges.
The BellmanFord algorithm is another widely used algorithm for finding the shortest path in a graph. Unlike Dijkstra’s algorithm, it can handle graphs with negative edge weights.
Conclusion
In summary, a directed graph is a data structure that represents a collection of nodes connected by directed edges. The directionality of the edges allows for more complex relationships between nodes, making it suitable for various applications such as routing algorithms, dependency analysis, and web page ranking. Understanding the properties and applications of directed graphs is essential for solving problems related to network analysis and optimization.