Data Structures Tutorial

Data Structures Tutorial Asymptotic Notation Structure and Union Array Data Structure Linked list Data Structure Type of Linked list Advantages and Disadvantages of linked list Queue Data Structure Implementation of Queue Stack Data Structure Implementation of Stack Sorting Insertion sort Quick sort Selection sort Heap sort Merge sort Bucket sort Count sort Radix sort Shell sort Tree Traversal of the binary tree Binary search tree Graph Spanning tree Linear Search Binary Search Hashing Collision Resolution Techniques

Misc Topic:

Priority Queue in Data Structure Deque in Data Structure Difference Between Linear And Non Linear Data Structures Queue Operations In Data Structure About Data Structures Data Structures Algorithms Types of Data Structures Big O Notations Introduction to Arrays Introduction to 1D-Arrays Operations on 1D-Arrays Introduction to 2D-Arrays Operations on 2D-Arrays Strings in Data Structures String Operations Application of 2D array Bubble Sort Insertion Sort Sorting Algorithms What is DFS Algorithm What Is Graph Data Structure What is the difference between Tree and Graph What is the difference between DFS and BFS Bucket Sort Dijkstra’s vs Bellman-Ford Algorithm Linear Queue Data Structure in C Stack Using Array Stack Using Linked List Recursion in Fibonacci Stack vs Array What is Skewed Binary Tree Primitive Data Structure in C Dynamic memory allocation of structure in C Application of Stack in Data Structures Binary Tree in Data Structures Heap Data Structure Recursion - Factorial and Fibonacci What is B tree what is B+ tree Huffman tree in Data Structures Insertion Sort vs Bubble Sort Adding one to the number represented an array of digits Bitwise Operators and their Important Tricks Blowfish algorithm Bubble Sort vs Selection Sort Hashing and its Applications Heap Sort vs Merge Sort Insertion Sort vs Selection Sort Merge Conflicts and ways to handle them Difference between Stack and Queue AVL tree in data structure c++ Bubble sort algorithm using Javascript Buffer overflow attack with examples Find out the area between two concentric circles Lowest common ancestor in a binary search tree Number of visible boxes putting one inside another Program to calculate the area of the circumcircle of an equilateral triangle Red-black Tree in Data Structures Strictly binary tree in Data Structures 2-3 Trees and Basic Operations on them Asynchronous advantage actor-critic (A3C) Algorithm Bubble Sort vs Heap Sort Digital Search Tree in Data Structures Minimum Spanning Tree Permutation Sort or Bogo Sort Quick Sort vs Merge Sort

Queue Data Structure

Queue in DS: The queue is a non-primitive and linear data structure. It works on the principle of FIFO (First In First Out). That is, the element that is added first, it is removed first, and the element that is added to the last, it is removed at the end.

Queue Data Structure

We often use a queue in our real world, let's see an example of this: - a person who is come first in the railway ticket reservation line and goes firstly, and another person who is engaged in the last and that person goes out at the end.

A queue has two ends, one is the front end, and the other is the rear end. The element is added to the rear end and removed from the front end.

The queue has the following conditions:

  1. If FRONT = 0, then the queue is empty.
  2. If REAR = size of the queue, then the queue is full.
  3. If FRONT = REAR, then there is at least one element in the queue.
  4. If you want to know the total number of elements in the queue, then you use this formula (REAR - FRONT) +1.

There are two primary operations in the queue.

  • Enqueue
  • Dequeue

When you insert an element in the queue, that process is called Enqueue, and when you remove an element from the queue, that process is called Dequeue.

Algorithm of Enqueue

This algorithm is used to add an element to the queue.

Initialize F = 0 and R = -1Check 0verflow             
If F = 0 and R = MAXSIZE or F = R + 1             
then write overflow and exit if F = NULL             
set F = 0 and R = 0                
else if R = MAXSIZE             
set R = 0
set R = R+1Queue[R] = itemExit

Algorithm of Dequeue

This algorithm is used to remove an element from the queue.

Check underflow    
if F < 0, write underflow and exit
set item = Queue[F]if F = R    
then set F = R = NULL   
else if F = MAXSIZE   
then set F = 0
set F = F+1exit

Types of Queue

  1. Linear Queue
  2. Circular Queue
  3. Priority Queue
  4. Dequeue (Double Ended Queue)

Linear queue: The data elements in the linear queue are organized one by one in sequential order. It works on the principle of FIFO. The performance of the linear queue is inefficient as compared to the circular queue.

Circular queue: Circular queue is also called ring-buffer. The last node of the circular queue is connected to the first node. It works on the principle of FIFO. In the circular queue, the element is added from the rear end and removed from the front end.

Priority Queue: A priority queue is a linear data structure in which every node has some priority that is processed by the following rules.

  • A higher priority element is processed before the lower priority element.
  • If two elements are of the same priority, then those elements are processed according to the sequence in the queue.
  • When deletion is performed, the element which has the highest priority removed first.
  • When the addition is performed, the element which has the highest priority added first.

Dequeue: The full name of the dequeue is a double-ended queue. Dequeue is a linear data structure in which you can add and remove the elements from both the front and back ends.

There are two types of dequeue:

  1. Input-restricted Dequeue
  2. Output-restricted Dequeue

Input-restricted Dequeue

In this queue, elements can be removed from both ends of the queue, but can only be inserted from one end.

Output-restricted Dequeue

In this queue, elements can be inserted from both ends of the queue, but can only be removed from one end.

Applications of Queue

  1. It is used in CPU scheduling and disk scheduling. When the CPU is required at the same time for multiple abstract processes, then the different CPU scheduling algorithms are used by implementing the queue.
  2. It is used to transfer the data between two processes in the asynchronous manner. In this, the queue is used for synchronization. For example - IO buffers, pipes, file IO, etc.
  3. It is also used in print spooling.
  4. It is also used in the graph and BFS (Breadth-First Search). BFS is an algorithm in the data structure that traverses and searches the graph.
  5. It is also used to handle interruptions in real-time systems.
  6. The call center phone systems also use the queue structure. It is used to hold the customer calls in order until an executive is free.

Implementation of Queue

You can implement the queue via the array, stack, and linked list. An array is the easiest way to implement the queue.

To implement queue via an array. 

  • Create an array of the n size. 
  • Initialize the value of the FRONT and REAR to 0. This value means that the array is currently empty.

In this, the first element of the array is FRONT, and the last element of the array is REAR. When you add the elements in the array, the index of the REAR increases, but the FRONT remains the same. The implementation of queue operations is shown below:

Queue Data Structure