# AdaptiSwarm-Edge

A Convergence-Accelerated Hybrid ACO-PSO Framework for Priority-Aware Dynamic Load Balancing in Heterogeneous Multi-Tier Edge Computing Networks.

## Files
- `sim.py` — Discrete-event simulation core (3-tier heterogeneous edge, Poisson arrivals, dynamic churn)
- `schedulers.py` — All schedulers: Round Robin, Least Connection, ACO, PSO, WOA, AdaptiSwarm-Edge, plus ablation variants
- `runner.py` — Episode runner with persistent pheromone state
- `convergence.py` — Fixed-instance convergence harness with shared fitness target
- `experiments.py` — Parallel experiment driver (30 runs per config, Wilcoxon tests, convergence figure)
- `make_tables.py` — LaTeX table + numeric macro generator from results.json

## Reproduction
```bash
pip install numpy scipy matplotlib
cd adaptiswarm
python experiments.py 30
python make_tables.py
# Paper compiles via: tectonic paper.tex (in paper/)
```

## Results
All numbers in the accompanying IEEE paper are generated by `make_tables.py` from `results.json` — no hand-entered results.