def cloudlab_config(cca,
end_time,
queue_size=1024,
btlbw=10,
rtt=40,
kind='iperf'):
config = {}
config['server'] = dict(HOST_SERVER._asdict())
config['client'] = dict(HOST_CLIENT._asdict())
config['experiments'] = {}
num_flows = [1]
# cca alone experiments
for num_cca_flows in num_flows:
experiment_name = '{}{}-{}bw-{}rtt-{}q'.format(cca, num_cca_flows,
btlbw, rtt, queue_size)
experiment = {'btlbw': btlbw, 'queue_size': queue_size}
experiment['flows'] = [{
'ccalg': cca,
'start_time': 0,
'end_time': end_time,
'rtt': rtt,
'kind': kind
} for _ in range(num_cca_flows)]
config['experiments'][experiment_name] = experiment
return config
def ccalg_predict_config(btlbw,
rtts,
end_time,
queue_sizes,
exp_name_suffix=None,
ccalgs=None,
loss=None):
config = {}
config['server'] = HOST_SERVER._asdict()
config['client'] = HOST_CLIENT._asdict()
config['experiments'] = {}
if ccalgs is None:
ccalgs = ['bbr', 'cubic', 'reno']
if loss is None:
loss = [None]
for rtt in rtts:
for queue_size in queue_sizes:
for ccalg in ccalgs:
for loss_rate in loss:
if exp_name_suffix is None:
experiment_name = '{}-{}bw-{}rtt-{}q'.format(
ccalg, btlbw, rtt, int(queue_size))
else:
experiment_name = '{}-{}bw-{}rtt-{}q-{}'.format(
ccalg, btlbw, rtt, int(queue_size),
exp_name_suffix)
if loss_rate is not None:
experiment_name = '{}-{}bw-{}rtt-{}q-{}loss-{}'.format(
ccalg, btlbw, rtt, int(queue_size),
float(loss_rate), exp_name_suffix)
experiment = {
'btlbw': btlbw,
'queue_size': int(queue_size),
'loss_rate': float(loss_rate)
}
else:
experiment = {
'btlbw': btlbw,
'queue_size': int(queue_size)
}
flows = [{
'ccalg': ccalg,
'start_time': 0,
'end_time': end_time,
'rtt': int(rtt)
}]
experiment['flows'] = flows
config['experiments'][experiment_name] = experiment
return config