Simulation

An agent-based simulation validates the theoretical claims of BPE. The simulation models a multi-source, multi-sink economy with heterogeneous agent capacities and task types.

Configuration

Parameter	Default	Description
Sources	10	Payment stream originators
Sinks	50	Capacity-declaring service agents
Task types	3	Heterogeneous service categories
Timesteps	1,000	Simulation horizon
EWMA $\alpha$	0.3	Capacity smoothing parameter

Experiments

1. Convergence & Efficiency

Measures allocation efficiency over time. BPE achieves 95.7% versus 93.5% for round-robin and 79.7% for random allocation.

2. Shock Response

Simulates 20% node-kill events and measures recovery time. BPE recovers within ~50 steps.

3. EWMA Sweep

Sensitivity analysis of the smoothing parameter $\alpha \in [0.05, 0.95]$ on allocation efficiency and stability.

4. Sybil Resistance

Confirms that stake fragmentation yields strictly negative net profit for all split counts $n > 1$ under the $\sqrt{\text{stake}}$ capacity cap.

5. Buffer Utilization

With overflow escrow sized at one period of peak demand, buffer stall rates drop from 73% to under 9%.

Running

cd simulation
python bpe_sim.py

Outputs are saved as PDF figures in docs/paper/figures/:

convergence.pdf - Allocation efficiency over time
shock.pdf - Shock response and recovery
ewma_sweep.pdf - EWMA parameter sensitivity
sybil.pdf - Sybil cost analysis
buffer.pdf - Buffer utilization dynamics

Source

Simulation source is on GitHub.