🚀 Smart Task Scheduler (Java)

A scalable, console-based Java task scheduler that demonstrates priority-based scheduling, concurrency control, and performance monitoring using core Java libraries.

This project focuses on systems-level thinking rather than UI, making it suitable for backend, systems, and internship-level interviews.

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📌 Overview

The Smart Task Scheduler is designed to manage and execute tasks based on priority and deadlines.
It simulates how real-world schedulers handle multiple jobs efficiently while balancing throughput, latency, and resource utilization.

The project emphasizes:

• Scheduling algorithms
• Java concurrency
• Performance metrics
• Clean system design

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✨ Key Features

🧠 Priority-Based Scheduling

• Tasks are assigned priorities (e.g., HIGH, MEDIUM, LOW)
• Higher-priority tasks are executed before lower-priority ones
• Internally uses a PriorityQueue with a custom comparator

⚙️ Concurrent Task Execution

• Tasks are executed concurrently using a fixed-size thread pool
• Prevents uncontrolled thread creation
• Demonstrates real-world resource management

📊 Execution Metrics & Monitoring

For each task:

• Start time
• End time
• Execution duration
• Execution status (SUCCESS / FAILED)

Aggregate metrics:

• Average execution time
• Total tasks executed
• Scheduler throughput

🛑 Graceful Shutdown

• Scheduler completes running tasks before shutting down
• New tasks are safely rejected after shutdown begins
• Prevents resource leaks and inconsistent states

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🧩 System Design

Core Components

• Task

  • Encapsulates task metadata
  • Stores priority, execution logic, and timing data

• Scheduler

  • Manages task queue
  • Controls concurrency using thread pools
  • Collects execution metrics

• Main

  • Demonstrates scheduler usage
  • Submits sample tasks
  • Displays execution logs and metrics

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🧪 Scheduling & Performance Insights

• Priority Scheduling

  • Improves response time for critical tasks
  • Can lead to starvation if not managed carefully

• Concurrency Trade-offs

  • Larger thread pools increase throughput
  • Smaller pools reduce contention and overhead

• Throughput vs Latency

  • Optimizing for throughput may increase individual task latency
  • Scheduler design balances both based on workload

These trade-offs are documented and observable through execution logs.

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🛠️ Tech Stack

• Java (Core)
• Java Collections Framework
• Java Concurrency Utilities (ExecutorService, PriorityQueue)

No external libraries or frameworks are used.

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▶️ How to Run

git clone https://github.com/samit-gupta/smart-task-scheduler-java
javac src/*.java
java src.Main

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🎯 Learning Outcomes

• Gained practical understanding of task scheduling algorithms and their real-world implications
• Learned to design priority-based systems using core Java data structures
• Hands-on experience with Java concurrency primitives and thread pool management
• Implemented execution metrics and monitoring to analyze system performance
• Improved skills in clean object-oriented design and separation of concerns
• Developed intuition around throughput vs latency trade-offs in concurrent systems

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👤 Author

Samit Gupta
B.Tech Computer Science and Engineering

• GitHub: https://github.com/samit-gupta
• LinkedIn: https://linkedin.com/in/samit-gupta

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🏆 Why This Project Matters

This project demonstrates core computer science fundamentals that are directly applicable to backend and systems engineering roles.

Instead of relying on frameworks or UI-heavy implementations, it focuses on:

• Scheduling theory
• Concurrency control
• Performance instrumentation
• System reliability

These concepts are commonly evaluated in internship and entry-level software engineering interviews, making this project both educational and interview-relevant.