def test(self,
trace: Trace,
save_dir: str,
plot_flag: bool = False) -> Tuple[float, float]:
"""Test a network trace and return rewards.
The 1st return value is the reward in Monitor Interval(MI) level and
the length of MI is 1 srtt. The 2nd return value is the reward in
packet level. It is computed by using throughput, average rtt, and
loss rate in each 500ms bin of the packet log. The 2nd value will be 0
if record_pkt_log flag is False.
Args:
trace: network trace.
save_dir: where a MI level log will be saved if save_dir is a
valid path. A packet level log will be saved if record_pkt_log
flag is True and save_dir is a valid path.
"""
links = [Link(trace), Link(trace)]
senders = [VivaceLatencySender(0, 0)]
net = Network(senders, links, self.record_pkt_log)
rewards = []
start_rtt = trace.get_delay(0) * 2 / 1000
run_dur = start_rtt
if save_dir:
os.makedirs(save_dir, exist_ok=True)
f_sim_log = open(
os.path.join(save_dir,
'{}_simulation_log.csv'.format(self.cc_name)),
'w', 1)
writer = csv.writer(f_sim_log, lineterminator='\n')
writer.writerow([
'timestamp', "send_rate", 'recv_rate', 'latency', 'loss',
'reward', "action", "bytes_sent", "bytes_acked", "bytes_lost",
"send_start_time", "send_end_time", 'recv_start_time',
'recv_end_time', 'latency_increase', "packet_size",
'bandwidth', "queue_delay", 'packet_in_queue', 'queue_size',
'cwnd', 'ssthresh', "rto", "packets_in_flight"
])
else:
f_sim_log = None
writer = None
while True:
net.run(run_dur)
mi = senders[0].get_run_data()
throughput = mi.get("recv rate") # bits/sec
send_rate = mi.get("send rate") # bits/sec
latency = mi.get("avg latency")
avg_queue_delay = mi.get("avg queue delay")
loss = mi.get("loss ratio")
reward = pcc_aurora_reward(
throughput / BITS_PER_BYTE / BYTES_PER_PACKET, latency, loss,
np.mean(trace.bandwidths) * 1e6 / BITS_PER_BYTE /
BYTES_PER_PACKET)
rewards.append(reward)
try:
ssthresh = senders[0].ssthresh
except:
ssthresh = 0
action = 0
if save_dir and writer:
writer.writerow([
net.get_cur_time(), send_rate, throughput, latency, loss,
reward, action, mi.bytes_sent, mi.bytes_acked,
mi.bytes_lost, mi.send_start, mi.send_end, mi.recv_start,
mi.recv_end,
mi.get('latency increase'), mi.packet_size,
links[0].get_bandwidth(net.get_cur_time()) *
BYTES_PER_PACKET * BITS_PER_BYTE, avg_queue_delay,
links[0].pkt_in_queue, links[0].queue_size,
senders[0].cwnd, ssthresh, senders[0].rto,
senders[0].bytes_in_flight / BYTES_PER_PACKET
])
if senders[0].srtt:
run_dur = senders[0].srtt
should_stop = trace.is_finished(net.get_cur_time())
if should_stop:
break
if f_sim_log:
f_sim_log.close()
if self.record_pkt_log and save_dir:
with open(
os.path.join(save_dir,
"{}_packet_log.csv".format(self.cc_name)),
'w', 1) as f:
pkt_logger = csv.writer(f, lineterminator='\n')
pkt_logger.writerow([
'timestamp', 'packet_event_id', 'event_type', 'bytes',
'cur_latency', 'queue_delay', 'packet_in_queue',
'sending_rate', 'bandwidth'
])
pkt_logger.writerows(net.pkt_log)
avg_sending_rate = senders[0].avg_sending_rate
tput = senders[0].avg_throughput
avg_lat = senders[0].avg_latency
loss = senders[0].pkt_loss_rate
pkt_level_reward = pcc_aurora_reward(tput,
avg_lat,
loss,
avg_bw=trace.avg_bw * 1e6 /
BITS_PER_BYTE / BYTES_PER_PACKET)
pkt_level_original_reward = pcc_aurora_reward(tput, avg_lat, loss)
if plot_flag and save_dir:
plot_simulation_log(
trace,
os.path.join(save_dir,
'{}_simulation_log.csv'.format(self.cc_name)),
save_dir, self.cc_name)
bin_tput_ts, bin_tput = senders[0].bin_tput
bin_sending_rate_ts, bin_sending_rate = senders[0].bin_sending_rate
lat_ts, lat = senders[0].latencies
plot(trace, bin_tput_ts, bin_tput, bin_sending_rate_ts,
bin_sending_rate,
tput * BYTES_PER_PACKET * BITS_PER_BYTE / 1e6,
avg_sending_rate * BYTES_PER_PACKET * BITS_PER_BYTE / 1e6,
lat_ts, lat, avg_lat * 1000, loss, pkt_level_original_reward,
pkt_level_reward, save_dir, self.cc_name)
if save_dir:
with open(
os.path.join(save_dir,
"{}_summary.csv".format(self.cc_name)), 'w',
1) as f:
summary_writer = csv.writer(f, lineterminator='\n')
summary_writer.writerow([
'trace_average_bandwidth', 'trace_average_latency',
'average_sending_rate', 'average_throughput',
'average_latency', 'loss_rate', 'mi_level_reward',
'pkt_level_reward'
])
summary_writer.writerow([
trace.avg_bw, trace.avg_delay,
avg_sending_rate * BYTES_PER_PACKET * BITS_PER_BYTE / 1e6,
tput * BYTES_PER_PACKET * BITS_PER_BYTE / 1e6, avg_lat,
loss,
np.mean(rewards), pkt_level_reward
])
return np.mean(rewards), pkt_level_reward
def _test(self, trace: Trace, save_dir: str, plot_flag: bool = False, saliency: bool = False):
reward_list = []
loss_list = []
tput_list = []
delay_list = []
send_rate_list = []
ts_list = []
action_list = []
mi_list = []
obs_list = []
if save_dir:
os.makedirs(save_dir, exist_ok=True)
f_sim_log = open(os.path.join(save_dir, 'aurora_simulation_log.csv'), 'w', 1)
writer = csv.writer(f_sim_log, lineterminator='\n')
writer.writerow(['timestamp', "target_send_rate", "send_rate",
'recv_rate', 'latency',
'loss', 'reward', "action", "bytes_sent",
"bytes_acked", "bytes_lost", "MI",
"send_start_time",
"send_end_time", 'recv_start_time',
'recv_end_time', 'latency_increase',
"packet_size", 'min_lat', 'sent_latency_inflation',
'latency_ratio', 'send_ratio',
'bandwidth', "queue_delay",
'packet_in_queue', 'queue_size', "recv_ratio", "srtt"])
else:
f_sim_log = None
writer = None
env = gym.make(
'PccNs-v0', traces=[trace], delta_scale=self.delta_scale, record_pkt_log=self.record_pkt_log)
env.seed(self.seed)
obs = env.reset()
grads = [] # gradients for saliency map
while True:
if isinstance(self.model, LoadedModel):
obs = obs.reshape(1, -1)
action = self.model.act(obs)
action = action['act'][0]
else:
if env.net.senders[0].got_data:
if saliency:
action, _states, grad = self.model.predict(
obs, deterministic=True, saliency=saliency)
grads.append(grad)
else:
action, _states = self.model.predict(
obs, deterministic=True)
else:
action = np.array([0])
# get the new MI and stats collected in the MI
# sender_mi = env.senders[0].get_run_data()
sender_mi = env.senders[0].history.back() #get_run_data()
max_recv_rate = env.senders[0].max_tput
throughput = sender_mi.get("recv rate") # bits/sec
send_rate = sender_mi.get("send rate") # bits/sec
latency = sender_mi.get("avg latency")
loss = sender_mi.get("loss ratio")
avg_queue_delay = sender_mi.get('avg queue delay')
sent_latency_inflation = sender_mi.get('sent latency inflation')
latency_ratio = sender_mi.get('latency ratio')
send_ratio = sender_mi.get('send ratio')
recv_ratio = sender_mi.get('recv ratio')
reward = pcc_aurora_reward(
throughput / BITS_PER_BYTE / BYTES_PER_PACKET, latency, loss,
trace.avg_bw * 1e6 / BITS_PER_BYTE / BYTES_PER_PACKET,
trace.avg_delay * 2/ 1e3)
if save_dir and writer:
writer.writerow([
env.net.get_cur_time(), round(env.senders[0].rate * BYTES_PER_PACKET * BITS_PER_BYTE, 0),
round(send_rate, 0), round(throughput, 0), latency, loss,
reward, action.item(), sender_mi.bytes_sent, sender_mi.bytes_acked,
sender_mi.bytes_lost, sender_mi.send_end - sender_mi.send_start,
sender_mi.send_start, sender_mi.send_end,
sender_mi.recv_start, sender_mi.recv_end,
sender_mi.get('latency increase'), sender_mi.packet_size,
sender_mi.get('conn min latency'), sent_latency_inflation,
latency_ratio, send_ratio,
env.links[0].get_bandwidth(
env.net.get_cur_time()) * BYTES_PER_PACKET * BITS_PER_BYTE,
avg_queue_delay, env.links[0].pkt_in_queue, env.links[0].queue_size,
recv_ratio, env.senders[0].estRTT])
reward_list.append(reward)
loss_list.append(loss)
delay_list.append(latency * 1000)
tput_list.append(throughput / 1e6)
send_rate_list.append(send_rate / 1e6)
ts_list.append(env.net.get_cur_time())
action_list.append(action.item())
mi_list.append(sender_mi.send_end - sender_mi.send_start)
obs_list.append(obs.tolist())
obs, rewards, dones, info = env.step(action)
if dones:
break
if f_sim_log:
f_sim_log.close()
if self.record_pkt_log and save_dir:
with open(os.path.join(save_dir, "aurora_packet_log.csv"), 'w', 1) as f:
pkt_logger = csv.writer(f, lineterminator='\n')
pkt_logger.writerow(['timestamp', 'packet_event_id', 'event_type',
'bytes', 'cur_latency', 'queue_delay',
'packet_in_queue', 'sending_rate', 'bandwidth'])
pkt_logger.writerows(env.net.pkt_log)
assert env.senders[0].last_ack_ts is not None and env.senders[0].first_ack_ts is not None
assert env.senders[0].last_sent_ts is not None and env.senders[0].first_sent_ts is not None
avg_sending_rate = env.senders[0].tot_sent / (env.senders[0].last_sent_ts - env.senders[0].first_sent_ts)
tput = env.senders[0].tot_acked / (env.senders[0].last_ack_ts - env.senders[0].first_ack_ts)
avg_lat = env.senders[0].cur_avg_latency
loss = 1 - env.senders[0].tot_acked / env.senders[0].tot_sent
pkt_level_reward = pcc_aurora_reward(tput, avg_lat,loss,
avg_bw=trace.avg_bw * 1e6 / BITS_PER_BYTE / BYTES_PER_PACKET)
pkt_level_original_reward = pcc_aurora_reward(tput, avg_lat, loss)
if self.record_pkt_log and plot_flag:
pkt_log = PacketLog.from_log(env.net.pkt_log)
plot_pkt_log(trace, pkt_log, save_dir, "aurora")
if plot_flag and save_dir:
plot_simulation_log(trace, os.path.join(save_dir, 'aurora_simulation_log.csv'), save_dir, self.cc_name)
bin_tput_ts, bin_tput = env.senders[0].bin_tput
bin_sending_rate_ts, bin_sending_rate = env.senders[0].bin_sending_rate
lat_ts, lat = env.senders[0].latencies
plot(trace, bin_tput_ts, bin_tput, bin_sending_rate_ts,
bin_sending_rate, tput * BYTES_PER_PACKET * BITS_PER_BYTE / 1e6,
avg_sending_rate * BYTES_PER_PACKET * BITS_PER_BYTE / 1e6,
lat_ts, lat, avg_lat * 1000, loss, pkt_level_original_reward,
pkt_level_reward, save_dir, self.cc_name)
if save_dir:
with open(os.path.join(save_dir, "{}_summary.csv".format(self.cc_name)), 'w', 1) as f:
summary_writer = csv.writer(f, lineterminator='\n')
summary_writer.writerow([
'trace_average_bandwidth', 'trace_average_latency',
'average_sending_rate', 'average_throughput',
'average_latency', 'loss_rate', 'mi_level_reward',
'pkt_level_reward'])
summary_writer.writerow(
[trace.avg_bw, trace.avg_delay,
avg_sending_rate * BYTES_PER_PACKET * BITS_PER_BYTE / 1e6,
tput * BYTES_PER_PACKET * BITS_PER_BYTE / 1e6, avg_lat,
loss, np.mean(reward_list), pkt_level_reward])
if saliency:
with open(os.path.join(save_dir, "saliency.npy"), 'wb') as f:
np.save(f, np.concatenate(grads))
return ts_list, reward_list, loss_list, tput_list, delay_list, send_rate_list, action_list, obs_list, mi_list, pkt_level_reward