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FOVNET (Fog-based Vehicular Network)

Intelligent Road Safety with Fog Computing

This project implements a vehicular communication system based on Fog Computing, developed and tested using the Eclipse MOSAIC 25.0 simulation framework. The system enables reliable, low-latency data exchange between vehicles (OBUs), Road-Side Units (RSUs), and a Fog node, with the ultimate goal of improving road safety.

For a better understanding of the project please read the article.

🚗 Project Purpose

The aim of this project is to design and simulate a custom multihop forwarding protocol to ensure robust connectivity between vehicles and the Fog server. By leveraging ad hoc V2X communication and central Fog processing, the system is capable of:

  • Creating a dynamic awareness map of neighboring vehicles,
  • Optimizing forwarding paths based on proximity and hop count,
  • Issuing real-time commands such as slow down, stop, or resume,
  • Reacting to emergency vehicles in traffic scenarios.

🔧 Technologies and Tools

  • Eclipse MOSAIC 25.0 — Co-simulation framework for mobility and communication networks.
  • SUMO (Simulation of Urban Mobility) — Used to simulate traffic behavior.
  • Java — Main programming language used for OBUs, RSUs, and the Fog node logic.
  • Ad hoc Networking (V2X) — Communication model for vehicles and RSUs.

📁 Project Structure


.
├── article/                  # Article diagrams and images
├── Network/                  # Java source files for OBUs, RSUs, Fog node, and messages
├── scenarios/                # MOSAIC scenarios
├── compile.sh                # Build script for the project
└── README.md

▶️ How to Run It

Requirements

Steps to Build and Run

  1. Edit the build script compile.sh: Set the following variables:

    BASE_DIR="/path/to/Network-Dir"
    TARGET_DIR="/path/to/eclipse-mosaic/scenario"
  2. Compile the project:

    ./compile.sh
  3. Run the scenario: From within the Eclipse MOSAIC root directory, execute:

    ./mosaic.sh -s vehApp_1

This will launch the simulation where regular vehicles yield to an emergency vehicle based on messages generated by the Fog.

🔍 Features Demonstrated

  • Dynamic neighbor map generation through Beacon and VehInfo messages
  • Multihop routing based on proximity and hop optimization
  • Emergency reaction through event-driven Fog messages
  • Vehicle behavior adapted in real time in a SUMO traffic environment

🧪 Future Work

The following improvements are planned:

  • Integration of knowledge-based opportunistic forwarding algorithms.
  • Evaluation and filtering of message freshness to prevent outdated data usage.
  • Unified message handling via abstract classes (e.g., Message superclass).
  • Statistical performance evaluation with metrics such as latency, throughput, and packet delivery using federation output.

👨‍💻 Authors

Developed by:

  • Augusto Campos (PG57510)
  • Carlos Silva (PG57518)

Novos Paradigmas de Rede, Maio 2025

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