Vehicular Edge Computing Simulation (DTOSC Algorithm)

A comprehensive co-simulation framework for modeling vehicular edge computing systems with dependency-aware task offloading and resource optimization.

Overview

This project implements a simulation environment combining:

• SUMO: Vehicle mobility simulation
• NS-3: Wireless network simulation
• Python: DTOSC algorithm implementation and orchestration

Project Structure

cc-project/
├── src/
│   ├── sumo/              # SUMO network and road network definitions
│   ├── ns3/               # NS-3 integration and custom modules
│   ├── algorithms/        # DTOSC and scheduling algorithms
│   └── utils/             # Helper utilities and data structures
├── config/                # Configuration files for simulations
├── scripts/               # Installation and execution scripts
├── docs/                  # Documentation and guides
├── results/               # Simulation results and outputs
└── README.md

System Requirements

• OS: Linux (Ubuntu 20.04 LTS or later recommended)
• RAM: Minimum 8GB (16GB recommended)
• Disk Space: 20GB for installation of tools and dependencies
• Compiler: GCC/G++ 9.0 or later

Quick Start

1. Prerequisites Installation

cd /home/sahil/Desktop/cc-project
chmod +x scripts/install_dependencies.sh
./scripts/install_dependencies.sh

2. Environment Setup

source setup_env.sh

3. Run Sample Simulation

python3 scripts/run_simulation.py --config config/sample_config.json

Detailed Setup Instructions

See SETUP_GUIDE.md for detailed installation instructions.

Key Components

DTOSC Algorithm

Implements dependency-aware task offloading and scheduling with:

• Task priority calculation based on DAG dependencies
• Knapsack-based caching optimization
• Power and frequency optimization

Simulation Orchestrator

Python-based central controller that:

• Manages SUMO vehicle mobility
• Communicates with NS-3 for network simulation
• Implements DTOSC scheduling decisions
• Collects and analyzes results

Integration Points

• SUMO-Python: TraCI API for vehicle position queries
• Python-NS-3: Custom socket-based communication protocol
• Result Analysis: CSV export and visualization tools

Configuration

See CONFIG_GUIDE.md for detailed configuration options.

Results & Analysis

Simulation results are stored in results/ directory:

• results/metrics.csv: Performance metrics
• results/traces.log: Detailed execution traces
• results/plots/: Visualization graphs

References

• SUMO: http://sumo.dlr.de/
• NS-3: https://www.nsnam.org/
• 3GPP TR 36.885: LTE-A V2X Specifications

License

This project is part of academic research. See LICENSE file for details.

Support

For issues and questions, refer to the documentation in docs/ or contact the maintainers.