Network Simulator

A Python-based GUI application for simulating computer networks using graph theory concepts. Implements link-state routing with Dijkstra's algorithm and provides visual network topology management.

Features

• Interactive GUI
  • Add/remove nodes and edges through intuitive interface
  • Visualize network topology with automatic layout
  • View forwarding tables for any node
• File I/O Support
  • Save/load network configurations in standardized format
  • Import/export network topologies
• Routing Features
  • Custom Dijkstra's algorithm implementation
  • Automatic forwarding table generation
  • Path cost calculations
• Error Handling
  • Comprehensive input validation
  • Clear error messages for invalid operations
• Modular Architecture
  • MVC design pattern implementation
  • Separate model-view-controller components
  • Extensible codebase

Installation

Prerequisites

• Python 3.8+
• pip package manager

Dependencies

pip install PyQt5 matplotlib networkx

Usage

Basic Operations

1. Adding Nodes
   • Select "Add Node" mode
   • Click on canvas to place node
   • Enter node name in dialog
2. Creating Edges
   • Select "Add Edge" mode
   • Click source node, then destination node
   • Enter edge weight in dialog
3. Viewing Forwarding Tables
   • Select "View Mode"
   • Click any node to see its forwarding table

File Operations

• Load Network: File → Open (Ctrl+O)
• Save Network: File → Save (Ctrl+S)
• Clear Network: File → New (Ctrl+N)

File Format

Network configurations are stored in .txt files with format:

nodes_count,edges_count
src_node,dest_node,weight
src_node,dest_node,weight
...

Example:

6,10
u,v,2
u,w,5
u,x,1
x,v,2
v,w,3
x,w,3
w,y,1
x,y,1
w,z,5
y,z,2

Implementation Details

Architecture

• Model: network_model.py

  • Manages graph data structure
  • Handles file I/O operations
  • Implements custom Dijkstra's algorithm

• View: network_view.py

  • Handles GUI presentation
  • Manages user interactions
  • Implements visualization using Matplotlib

• Controller: network_controller.py

  • Mediates between Model and View
  • Handles application logic
  • Manages event handling

Algorithm

• Custom Dijkstra's implementation features:
  • Priority queue optimization
  • O((E+V) log V) time complexity
  • Path reconstruction with next-hop tracking
  • Disconnected node handling