Memory Allocation First Fit Simulation

Technologies Used

Overview

This project is a Python-based interactive Jupyter Notebook that simulates memory allocation using the First Fit algorithm and Round-Robin CPU scheduling. It features a GUI built with ipywidgets, matplotlib for real-time visualization, and a benchmarking component to analyze performance.

Core Logic and Classes

• Process Class: Represents a job with attributes for size and remaining execution time.
• MemoryNode Class: Inherits from a generic doubly linked list Node class to represent individual memory blocks (either free or allocated to a Process).
• Memory Class: The memory manager. It maintains a linked list of MemoryNodes and implements the core algorithms:
  • allocate(process): Implements the First Fit algorithm by traversing the list to find the first free block large enough.
  • coalesce(): Merges adjacent free memory blocks to reduce external fragmentation.
  • compact(): Rearranges memory by moving all allocated blocks to one end.
• Processor Class: The CPU scheduler. Its run() method contains the main simulation loop, implementing Round-Robin scheduling with a time quantum of 1. It orchestrates process allocation, execution, deallocation, and triggers memory management routines at specified intervals.

Interactive Components

• UI (ipywidgets): An interface built with sliders, text inputs, and buttons allows users to configure simulation parameters like memory size, number of processes, and the timing intervals for compaction and coalescing.
• Visualization (matplotlib): At each time step, a horizontal bar chart is generated to represent the memory state, with different colors for allocated and free blocks, providing a clear visual trace of the simulation.