def parse_network(self) -> dict:
"""
Converts the NetworkX network in the simulator to a dict in a format specified in the SimulatorState class.
"""
max_node_usage = metrics.get_metrics()['run_max_node_usage']
self.network_dict = {'nodes': [], 'edges': []}
for node in self.params.network.nodes(data=True):
node_cap = node[1]['cap']
run_max_node_usage = max_node_usage[node[0]]
# 'used_resources' here is the max usage for the run.
self.network_dict['nodes'].append({
'id':
node[0],
'resource':
node_cap,
'used_resources':
run_max_node_usage
})
for edge in self.network.edges(data=True):
edge_src = edge[0]
edge_dest = edge[1]
edge_delay = edge[2]['delay']
edge_dr = edge[2]['cap']
# We use a fixed user data rate for the edges here as the functionality is not yet incorporated in the
# simulator.
# TODO: Implement used edge data rates in the simulator.
edge_used_dr = 0
self.network_dict['edges'].append({
'src': edge_src,
'dst': edge_dest,
'delay': edge_delay,
'data_rate': edge_dr,
'used_data_rate': edge_used_dr
})
def test_simulator(self):
"""
Test the simulator
"""
# Collect metrics
self.metric_collection = metrics.get_metrics()
# Check if Simulator is initiated correctly
self.assertIsInstance(self.flow_simulator, FlowSimulator)
# Check if Params are set correctly
self.assertIsInstance(self.simulator_params, SimulatorParams)
# Check if generated flows are equal to processed flow + dropped + active flows
gen_flow_check = self.metric_collection['generated_flows'] == (self.metric_collection['processed_flows'] +
self.metric_collection['dropped_flows'] +
self.metric_collection['total_active_flows'])
self.assertIs(gen_flow_check, True)
def network_metrics(self):
"""
Processes the metrics and parses them in a format specified in the SimulatorState class.
"""
stats = metrics.get_metrics()
self.traffic = stats['run_total_requested_traffic']
self.network_stats = {
'total_flows': stats['generated_flows'],
'successful_flows': stats['processed_flows'],
'dropped_flows': stats['dropped_flows'],
'in_network_flows': stats['total_active_flows'],
'avg_end2end_delay': stats['avg_end2end_delay'],
'run_avg_end2end_delay': stats['run_avg_end2end_delay'],
'run_max_end2end_delay': stats['run_max_end2end_delay'],
'run_total_processed_traffic': stats['run_total_processed_traffic']
}