Scheduling criteria (turnaround time, waiting time, throughput) in Operating Systems - Mini Project: Build & Apply

Understanding Scheduling Criteria: Turnaround Time, Waiting Time, and Throughput

📖 Scenario: You are managing a small computer system that runs several tasks. Each task has a specific time it needs to run (burst time). You want to understand how well your system schedules these tasks by calculating key performance measures.

🎯 Goal: Build a simple data structure to hold task details, set a total time limit, calculate turnaround time, waiting time, and throughput for the tasks, and finalize the summary of these scheduling criteria.

📋 What You'll Learn

Create a dictionary with task names as keys and their burst times as values.

Add a variable for the total time available for processing tasks.

Calculate turnaround time and waiting time for each task using a simple scheduling order.

Calculate throughput as the number of tasks completed per unit time.

Summarize the scheduling criteria in a final dictionary.

💡 Why This Matters

🌍 Real World

Scheduling criteria like turnaround time, waiting time, and throughput help system administrators and developers understand how efficiently a computer system handles multiple tasks.

💼 Career

Knowledge of scheduling criteria is essential for roles in system administration, software development, and performance engineering to optimize resource use and improve user experience.

1

DATA SETUP: Create the tasks dictionary

Create a dictionary called tasks with these exact entries: 'Task1': 4, 'Task2': 3, 'Task3': 2, 'Task4': 1 representing the burst time for each task.

Operating Systems

# Create the tasks dictionary with burst times
# Your code here

Need a hint?

Use curly braces to create a dictionary with task names as keys and numbers as values.

2

CONFIGURATION: Set the total available time

Add a variable called total_time and set it to 10 representing the total time available to run all tasks.

Operating Systems

tasks = {'Task1': 4, 'Task2': 3, 'Task3': 2, 'Task4': 1}
# Set the total available time
# Your code here

Need a hint?

Just create a variable and assign the number 10 to it.

3

CORE LOGIC: Calculate turnaround time and waiting time

Create two dictionaries called turnaround_time and waiting_time. Use a variable elapsed starting at 0. For each task in the order Task1, Task2, Task3, Task4, calculate turnaround time as elapsed + burst time and waiting time as elapsed. Update elapsed by adding the current task's burst time after each calculation.

Operating Systems

tasks = {'Task1': 4, 'Task2': 3, 'Task3': 2, 'Task4': 1}
total_time = 10
# Calculate turnaround_time and waiting_time dictionaries
# Your code here

Need a hint?

Use a for loop over the list of tasks in order. Keep track of elapsed time and update both dictionaries inside the loop.

4

COMPLETION: Calculate throughput and summarize criteria

Create a variable called throughput as the number of tasks divided by total_time. Then create a dictionary called scheduling_summary with keys 'Turnaround Time', 'Waiting Time', and 'Throughput' holding the respective dictionaries and value.

Operating Systems

tasks = {'Task1': 4, 'Task2': 3, 'Task3': 2, 'Task4': 1}
total_time = 10
turnaround_time = {}
waiting_time = {}
elapsed = 0
for task in ['Task1', 'Task2', 'Task3', 'Task4']:
    waiting_time[task] = elapsed
    elapsed += tasks[task]
    turnaround_time[task] = elapsed
# Calculate throughput and create scheduling_summary dictionary
# Your code here

Need a hint?

Count the tasks with len(tasks) and divide by total_time. Then create a dictionary with the three keys and their values.