Try SimulatorDynamicCPUSchedulingSimulator
An interactive visualization tool that brings Operating System scheduling concepts to life through real-time simulation and analysis.
Problem Statement
The Challenge: Understanding CPU scheduling algorithms is fundamental to Operating Systems education, yet traditional learning methods rely on static diagrams and manual calculations that fail to convey the dynamic nature of process scheduling.
The Gap: Students struggle to visualize how different algorithms behave under varying workloads, compare their performance metrics, and understand the trade-offs between efficiency, fairness, and overhead.
Our Solution: A real-time, interactive simulator that visualizes CPU scheduling algorithms with animated Gantt charts, live performance metrics, and intelligent algorithm recommendations.
Why CPU Scheduling Matters
CPU scheduling is the cornerstone of multiprogramming operating systems. It determines system performance, responsiveness, and resource utilization.
Resource Utilization
Maximize CPU usage to ensure the processor is never idle when processes are waiting.
Throughput
Complete as many processes as possible per unit time for efficient batch processing.
Turnaround Time
Minimize the total time from process submission to completion.
Waiting Time
Reduce time processes spend in the ready queue waiting for CPU allocation.
Response Time
Ensure quick first response for interactive systems and user experience.
Fairness
Guarantee all processes receive fair share of CPU time without starvation.
Project Objectives
Interactive Visualization
Create animated Gantt charts that show real-time process execution and context switches.
Multiple Algorithms
Implement FCFS, SJF (Preemptive), Round Robin, and Priority Scheduling with accurate behavior.
Performance Metrics
Calculate and display waiting time, turnaround time, throughput, and context switches.
Smart Optimization
Build an intelligent system that detects suboptimal scheduling and suggests better algorithms.
Educational Tool
Provide clear explanations and comparisons to help students understand trade-offs.
Modern Experience
Deliver a polished, responsive web application with smooth animations and intuitive UX.
Feasibility & Scope
In Scope
- ✓FCFS, SJF, Round Robin, Priority algorithms
- ✓Real-time Gantt chart visualization
- ✓Performance metrics calculation
- ✓Smart algorithm switching
- ✓Responsive web interface
- ✓REST API backend
Technical Feasibility
- ◆Browser-based: No installations required
- ◆Modern tech stack: React, TypeScript, Node.js
- ◆Lightweight: Fast load times, smooth animations
- ◆Scalable: Can add more algorithms easily
- ◆Educational: Suitable for classroom use
- ◆Open source: Fully transparent codebase
Scheduling Algorithms
Our simulator implements four fundamental CPU scheduling algorithms, each with distinct characteristics and use cases.
First Come First Serve
The simplest scheduling algorithm. Processes are executed in the exact order they arrive in the ready queue.
Formula: Waiting Time = Start Time - Arrival Time
Best for: Batch processing systems where simplicity is preferred over efficiency.
✓ Advantages
- • Simple to implement
- • No starvation
- • Fair in terms of arrival order
✗ Disadvantages
- • Convoy effect
- • High average waiting time
- • Not optimal for interactive systems
Shortest Job First
Selects the process with the smallest remaining burst time. Our implementation uses preemptive SJF (Shortest Remaining Time First).
Formula: Always picks min(remaining_burst_time)
Best for: Systems where burst times are predictable and minimizing wait time is critical.
✓ Advantages
- • Minimum average waiting time
- • Optimal for batch systems
- • Efficient CPU utilization
✗ Disadvantages
- • Requires burst time prediction
- • May cause starvation
- • Overhead of tracking remaining time
Round Robin
Each process gets a fixed time slice (quantum). After the quantum expires, the process is moved to the back of the queue.
Formula: Context Switches ≈ Total Burst / Quantum
Best for: Time-sharing systems and interactive applications requiring responsiveness.
✓ Advantages
- • Fair CPU allocation
- • Good response time
- • No starvation
✗ Disadvantages
- • High context switch overhead
- • Performance depends on quantum
- • Higher turnaround for long processes
Priority Scheduling
Each process is assigned a priority. The CPU is allocated to the process with the highest priority (lower number = higher priority).
Formula: Next Process = min(priority) from ready queue
Best for: Real-time systems where certain processes must complete before others.
✓ Advantages
- • Flexible prioritization
- • Good for real-time systems
- • Important tasks run first
✗ Disadvantages
- • May cause starvation
- • Priority inversion problem
- • Requires priority assignment logic
Implementation Progress
Completed Features
- ✓FCFS Algorithm - Non-preemptive, arrival-order execution
- ✓SJF Algorithm - Preemptive (SRTF) with dynamic re-evaluation
- ✓Round Robin - Time-sliced execution with configurable quantum
- ✓Priority Scheduling - Non-preemptive priority-based selection
- ✓Smart Switcher - Automatic algorithm optimization
- ✓Metrics Engine - Wait time, turnaround, context switches
- ✓Gantt Chart - Animated timeline visualization
- ✓Real-time Updates - Live results as inputs change
- ✓Modern UI - Dark theme with smooth animations
- ✓REST API - Express backend with TypeScript
Tech Stack
React 18
UI Library
TypeScript
Type Safety
Vite
Build Tool
Tailwind
Styling
Framer Motion
Animations
MUI Charts
Data Viz
Express
Backend
Node.js
Runtime
System Architecture
Frontend
React SPA with real-time updates
- Landing Page (Presentation)
- Simulator Page (Input + Results)
- Gantt Chart Component
- MUI X Charts Integration
- Framer Motion Animations
API Layer
RESTful endpoints for simulation
- POST /api/simulate
- Request validation
- Algorithm routing
- Response formatting
- Error handling
Backend Logic
Core algorithms & metrics engine
- FCFS, SJF, RR, Priority
- Metrics Calculator
- Smart Switcher/Evaluator
- Gantt Chart Generator
- Process Result Builder
Data Flow Pipeline
Key Formulas & Metrics
Completion Time (CT)
Time when process finishes
Example: CT = End time in Gantt chart
Turnaround Time (TAT)
CT - Arrival Time
Example: TAT = 10 - 2 = 8 units
Waiting Time (WT)
TAT - Burst Time
Example: WT = 8 - 5 = 3 units
Average Waiting Time
Σ(WT) / n
Example: (3 + 5 + 2) / 3 = 3.33
Throughput
n / Total Time
Example: 5 processes / 20 units = 0.25
CPU Utilization
(Busy Time / Total Time) × 100
Example: (18 / 20) × 100 = 90%
OS Concepts Demonstrated
CPU Scheduling
Algorithm selection, process ordering, ready queue management
Context Switching
Process state saving, overhead measurement, switch optimization
Performance Metrics
Wait time, turnaround time, throughput, CPU utilization
Process Management
Process states, arrival modeling, burst time simulation
Time Quantum
Time-slicing, preemption intervals, quantum selection
Priority Systems
Priority assignment, scheduling decisions, starvation prevention
Optimization
Algorithm comparison, trade-off analysis, workload adaptation
Preemption
Preemptive vs non-preemptive, SRTF implementation, state management
Smart Algorithm Switching
Our intelligent evaluator detects suboptimal scheduling and automatically recommends better algorithms.
Round Robin → SJF
When context switches exceed threshold:
// Detection
if (contextSwitches > processes.length × 2.5)
→ Switch to SJF
Example
"Round Robin caused 8 context switches. System switched to SJF to reduce turnaround time by 25%."
FCFS → SJF
When convoy effect causes high waiting time:
// Detection
if (fcfsWaitTime > sjfWaitTime × 2)
→ Switch to SJF
Example
"FCFS led to high average waiting time (12.5). System switched to SJF (avg waiting: 4.2)."
Experience the Simulator
Configure processes, select an algorithm, and watch the scheduling unfold in real-time with animated Gantt charts and live metrics.