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MultiRATVANET Framework

Multi-RAT VANET Handover Simulation Framework for OMNeT++ / Veins / SUMO / INET / Simu5G

A vehicle carries multiple radio access technologies (DSRC, WiFi, LTE, 5G-NR) simultaneously, all terminating at a unified IPv4 stack. An application-layer RAT selector orchestrates handovers based on configurable policies, enabling research into multi-RAT vehicular network optimization.

Quick Start

# Build
./tools/build.sh

# Run a scenario
./tools/run.sh Highway_CoveragePriority --sim-time-limit=70s

# Analyze results
python tools/analysis/plot-residency.py results/

Documentation

Features

  • ✅ Multiple RATs: DSRC, WiFi, LTE, 5G-NR, 6G placeholder
  • ✅ Flexible policies: Coverage Priority, SINR-based, Latency-QoS, Load-Balanced, Ensemble Voting, ML-driven
  • ✅ Realistic scenarios: Highway (baseline), UrbanGrid (synthetic), ElectronicCity (real OSM)
  • ✅ Full V2X support: CAM/DENM broadcasts, V2N upload/download
  • ✅ Comprehensive KPIs: Handover count, latency, ping-pong ratio, RAT residency, packet loss
  • ✅ Automated tools: Single-command build & run
  • ✅ CI/CD ready: GitHub Actions workflows included
  • ✅ Docker support: Reproducible environment

Prerequisites

  • OMNeT++ 5.6.1 (built)
  • INET 4.2.2 (built)
  • Veins 5.2 + veins_inet (built)
  • Simu5G 1.1.0 (built)
  • SUMO 1.24+ (on PATH)
  • Python 3.8+ (for analysis tools)

Repository Structure

framework/               Core MultiRATVANET code
├── src/multirat/
│   ├── base/           Types, metrics, constants
│   ├── core/           NED nodes & networks
│   ├── monitor/        Coverage, SINR, latency detection
│   ├── manager/        Handover logic & statistics
│   ├── policies/       RAT selection strategies
│   └── apps/           V2V, V2X applications

simulations/            OMNeT++ simulation config
├── networks/           Network topologies (NED)
├── scenarios/          Configuration by scenario (INI)
└── omnetpp.ini        Master configuration

sumo/                   SUMO traffic models
├── highway/
├── urbangrid/
└── electroniccity/

docs/                   Comprehensive documentation
tools/                  Build, run, analysis automation
tests/                  Unit & integration tests
results/                Experiment results & analysis

Build & Run

# Compile framework
cd framework
opp_makemake -f --deep -O out -L [framework_paths]
make -j4

# Run scenario
cd ..
./tools/run.sh UrbanGrid_Ensemble --sim-time-limit=120s

# Analyze results
python tools/analysis/export-results.py results/
python tools/analysis/plot-metrics.py results/

Configuration

Each scenario has multiple configurations:

Highway_CoveragePriority      Fixed priority (DSRC > WiFi > NR > LTE)
Highway_Ensemble              Multi-objective voting
Highway_ML                    ML agent hook
UrbanGrid_*                   Similar variants
ElectronicCity_*              Real-world scenario

Modify simulations/scenarios/*/config.ini to adjust:

  • Vehicle density & routes
  • Infrastructure positions & coverage
  • RAT parameters (bandwidth, delay, power)
  • Policy hysteresis & thresholds
  • Handover decision interval

Results & Analysis

Results saved per run:

results/<Scenario>_<Config>_<timestamp>/
├── run-settings.ini         Config snapshot
├── *.sca                    Statistics
├── *.vec                    Time-series vectors
└── analysis/
    ├── summary.csv          Aggregated KPIs
    └── plots/               Generated plots

Export & analyze:

python tools/analysis/export-results.py results/*/
python tools/analysis/plot-handovers.py results/*/
python tools/analysis/statistical-summary.py results/*/

Contributing

See CONTRIBUTING.md for guidelines.

License

Research license — see LICENSE

Citation

If you use MultiRATVANET in your research, please cite:

[Your citation here when published]

Support

  • Issues: GitHub Issues
  • Documentation: See docs/INDEX.md
  • Troubleshooting: See docs/TROUBLESHOOTING.md

Built with: OMNeT++ • INET • Veins • Simu5G • SUMO

Maintained by: [Your Team/Lab]

Last Updated: September 2026

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