Scalability Tests
Results from scalability tests with up to 100,000 agents.
Near-linear scaling up to 10,000 agents.
Performance degradation at large scales and mitigations.
Resilience Testing
Network’s ability to maintain performance under random node failures.
92% performance retention under 30% agent failure.
Heat Map Analysis
Visualization of dynamic load balancing in the network.
Code Example: Performance Testing
import random
import numpy as np
# Simulate node failure in the network
def node_failure(network, failure_rate):
failed_nodes = random.sample(network.nodes(), int(failure_rate * len(network.nodes())))
network.remove_nodes_from(failed_nodes)
return network
# Example: simulate 30% node failure
G = nx.erdos_renyi_graph(1000, 0.05)
G_failed = node_failure(G, 0.3)