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

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.