🚀 Distributed Task Management System

This project is a cloud-based simulation that manages tasks across distributed virtual machines (VMs). It incorporates concepts of cloud computing, multithreading, and virtual disk storage to create a robust system for task management.

🌟 Features

• ✅ Add, update, delete, and retrieve tasks for each VM.
• 💾 Persistent task storage using a simulated virtual disk.
• 🧠 Dual-core CPU simulation for parallel task processing.
• 🌐 Commands processed via a centralized cloud system.
• 🔍 Retrieve processed tasks from both memory and virtual disk.

🛠️ Technologies Used

• 🐍 Python: Programming language.
• 🧱 Object-Oriented Programming (OOP): For modular and scalable design.
• ⚙️ Multithreading: To simulate CPU cores.
• 📂 File-based Storage: To simulate virtual disk operations.

📖 How It Works

1. 💻 Client Commands: Commands are issued through the client.py script.
2. ☁️ Cloud Processing: Commands are processed by the cloud.py module and routed to the appropriate VM.
3. 📂 Task Storage: Tasks are processed and stored in both memory and a virtual disk.

📝 Commands

• ➕ Add a Task:

  python client.py add-task <vm_id> <task_data> <task_id>
  

• 📋 List Tasks:

  python client.py list-tasks <vm_id>
  

• ❌ Delete a Task:

  python client.py delete-task <vm_id> <task_id>
  

• ✏️ Update a Task:

  python client.py update-task <vm_id> <task_id> <new_data>
  

• 🧐 Get Processed Tasks:

  python client.py get-processed-tasks <vm_id>
  

• 📂 List All Tasks (Stored on Disk):

  python client.py list-all-tasks <vm_id>
  

• 🧹 Clear Disk:

  python client.py clear-disk <vm_id>