algorithm on multiple queues in a single dimensional array
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Usually it's modelled by the function (alpha)e^(-alpha *x).
The Breadth-First Search (BFS) algorithm can be implemented using recursion by using a queue data structure to keep track of the nodes to visit. The algorithm starts by adding the initial node to the queue and then recursively visits each neighbor of the current node, adding them to the queue. This process continues until all nodes have been visited.
Add weights to the elements of the queue and use an algorithm to sort the queue every time an element is added.
The time complexity of Dijkstra's algorithm with a priority queue data structure is O((V E) log V), where V is the number of vertices and E is the number of edges in the graph.
Windows XP uses a quantum-based, preemptive priority scheduling algorithm
Breadth-first search
In queue insertion takes place on rear end and deletion takes place on front end. INSERTION(QUEUE,N,FRONT,REAR,ITEM) :QUEUE is the name of a array on which we are implementing the queue having size N. view comlete ans at http://mcabcanotes.in/algorithm-to-perform-insertion-and-deletion-in-a-queue/
By far the simplest CPU-scheduling algorithm is the first-come, first-served (FCFS) scheduling algorithm. With this scheme, the process that requests the CPU first is allocated the CPU first. The implementation of the FCFS policy is easily managed with a FIFO queue. When a process enters the ready queue, its PCB is linked onto the tail of the queue. When the CPU is free, it is allocated to the process at the head of the queue. The running process is then removed from the queue. The code for FCFS scheduling is simple to write and understand. The average waiting time under the FCFS policy, however, is often quite long. Consider the following set of processes that arrive at time 0, with the length of the CPU-burst time given in milliseconds:
Delete Front---- DQDELETE_FRONT(QUEUE, FRONT, REAR, ITEM) 1. [check for queue underflow] If FRONT<0, Then: Print: "Queue is empty", and Return. 2. ITEM = QUEUE[FRONT]; 3. Set FRONT = FRONT + 1. 4. Return. Delete Rear---- DQDELETE_REAR(QUEUE, REAR, FRONT, ITEM) 1. [check for queue underflow] If REAR<0, Then: Print: "Queue is empty", and Return. 2. ITEM = QUEUE[REAR]. 3. Set REAR = REAR - 1. 4.Return.
The runtime complexity of the Dijkstra algorithm is O(V2) with a simple implementation using an adjacency matrix, or O(E V log V) with a more efficient implementation using a priority queue.