def __init__(self, history_len=10,
features="sent latency inflation,latency ratio,send ratio",
congestion_control_type="rl", log_dir=""):
"""Network environment used in simulation.
congestion_control_type: rl is pcc-rl. cubic is TCPCubic.
"""
assert congestion_control_type in {"rl", "cubic"}, \
"Unrecognized congestion_control_type {}.".format(
congestion_control_type)
random.seed(42)
self.log_dir = log_dir
self.congestion_control_type = congestion_control_type
if self.congestion_control_type == 'rl':
self.use_cwnd = False
elif self.congestion_control_type == 'cubic':
self.use_cwnd = True
self.viewer = None
self.rand = None
self.min_bw, self.max_bw = (100, 500) # packet per second
self.min_lat, self.max_lat = (0.05, 0.5) # latency second
self.min_queue, self.max_queue = (0, 8)
self.min_loss, self.max_loss = (0.0, 0.05)
self.history_len = history_len
# print("History length: %d" % history_len)
self.features = features.split(",")
# print("Features: %s" % str(self.features))
self.links = None
self.senders = None
self.create_new_links_and_senders()
self.net = Network(self.senders, self.links)
self.run_dur = None
self.run_period = 0.1
self.steps_taken = 0
self.max_steps = MAX_STEPS
self.debug_thpt_changes = False
self.last_thpt = None
self.last_rate = None
if self.use_cwnd:
self.action_space = spaces.Box(np.array([-1e12, -1e12]), np.array([1e12, 1e12]), dtype=np.float32)
else:
self.action_space = spaces.Box(np.array([-1e12]), np.array([1e12]), dtype=np.float32)
self.observation_space = None
use_only_scale_free = True
single_obs_min_vec = sender_obs.get_min_obs_vector(self.features)
single_obs_max_vec = sender_obs.get_max_obs_vector(self.features)
self.observation_space = spaces.Box(np.tile(single_obs_min_vec, self.history_len),
np.tile(single_obs_max_vec, self.history_len),
dtype=np.float32)
self.reward_sum = 0.0
self.reward_ewma = 0.0
self.event_record = {"Events":[]}
self.episodes_run = -1
print('event_id,event_type,next_hop,cur_latency,event_time,next_hop,dropped,event_q_length,send_rate,duration')
def __init__(self,
history_len=arg_or_default("--history-len", default=10),
features=arg_or_default("--input-features",
default="sent latency inflation," +
"latency ratio," + "send ratio")):
self.viewer = None
self.rand = None
self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.sock.setblocking(1)
self.sock.bind(("localhost", 9787))
self.conn = None
self.conn_addr = None
self.features = features.split(",")
self.history_len = history_len
self.history = sender_obs.SenderHistory(history_len, self.features, 0)
self.rate = STARTING_RATE
single_obs_min_vec = sender_obs.get_min_obs_vector(self.features)
single_obs_max_vec = sender_obs.get_max_obs_vector(self.features)
self.observation_space = spaces.Box(np.tile(single_obs_min_vec,
self.history_len),
np.tile(single_obs_max_vec,
self.history_len),
dtype=np.float32)
self.action_space = spaces.Box(np.array([-1e12]),
np.array([1e12]),
dtype=np.float32)
self.steps_taken = 0
self.reward_sum = 0.0
self.reward_ewma = 0.0
def __init__(self,
history_len=arg_or_default("--history-len", default=10),
features=arg_or_default("--input-features",
default="sent latency inflation," +
"latency ratio," + "send ratio")):
self.viewer = None
self.rand = None
self.min_bw, self.max_bw = (100, 500) # bandwidth
self.min_lat, self.max_lat = (0.05, 0.5) # latency
self.min_queue, self.max_queue = (0, 8)
self.min_loss, self.max_loss = (0.0, 0.05)
self.history_len = history_len
print("History length: %d" % history_len)
self.features = features.split(",")
print("Features: %s" % str(self.features))
self.links = None
self.senders = None
self.create_new_links_and_senders()
self.net = Network(self.senders, self.links)
self.run_dur = None
self.run_period = 0.1
self.steps_taken = 0
self.max_steps = MAX_STEPS
self.debug_thpt_changes = False
self.last_thpt = None
self.last_rate = None
# define action space
if USE_CWND:
self.action_space = spaces.Box(np.array([-1e12, -1e12]),
np.array([1e12, 1e12]),
dtype=np.float32)
else:
self.action_space = spaces.Box(np.array([-1e12]),
np.array([1e12]),
dtype=np.float32)
# define observation space
use_only_scale_free = True
single_obs_min_vec = sender_obs.get_min_obs_vector(self.features)
single_obs_max_vec = sender_obs.get_max_obs_vector(self.features)
self.observation_space = spaces.Box(np.tile(single_obs_min_vec,
self.history_len),
np.tile(single_obs_max_vec,
self.history_len),
dtype=np.float32)
self.reward_sum = 0.0
self.reward_ewma = 0.0
self.event_record = {"Events": []}
self.episodes_run = -1
def __init__(self, env_config=None):
print("Simulator for data center networks")
self.viewer = None
self.rand = None
# 10G to 50G
self.min_bw, self.max_bw = (MIN_RATE, MAX_RATE)
# 100ns to 500ns
self.min_lat, self.max_lat = (1e-7, 5e-7)
# shallow buffer
self.min_queue, self.max_queue = (0, 3)
# ultra-low loss
self.min_loss, self.max_loss = (0.0, 0.0005)
self.history_len = env_config['history_len']
print("History length: %d" % self.history_len)
self.features = env_config['features'].split(",")
print("Features: %s" % str(self.features))
self.links = None
self.senders = None
self.create_new_links_and_senders()
self.net = Network(self.senders, self.links)
self.run_dur = None
self.run_period = 0.1
self.steps_taken = 0
self.max_steps = MAX_STEPS
self.debug_thpt_changes = False
self.last_thpt = None
self.last_rate = None
if USE_CWND:
self.action_space = spaces.Box(np.array([-1e12, -1e12]),
np.array([1e12, 1e12]),
dtype=np.float32)
else:
self.action_space = spaces.Box(np.array([-1e12]),
np.array([1e12]),
dtype=np.float32)
self.observation_space = None
use_only_scale_free = True
single_obs_min_vec = sender_obs.get_min_obs_vector(self.features)
single_obs_max_vec = sender_obs.get_max_obs_vector(self.features)
self.observation_space = spaces.Box(np.tile(single_obs_min_vec,
self.history_len),
np.tile(single_obs_max_vec,
self.history_len),
dtype=np.float32)
self.reward_sum = 0.0
self.reward_ewma = 0.0
self.event_record = {"Events": []}
self.episodes_run = -1
def __init__(
self,
trace_scheduler: Scheduler,
history_len: int = 10,
# features="sent latency inflation,latency ratio,send ratio",
features: List[str] = [
"sent latency inflation", "latency ratio", "recv ratio"
],
record_pkt_log: bool = False):
"""Network environment used in simulation."""
self.record_pkt_log = record_pkt_log
self.trace_scheduler = trace_scheduler
self.current_trace = self.trace_scheduler.get_trace()
self.history_len = history_len
self.features = features
# construct sender and network
self.links = [Link(self.current_trace), Link(self.current_trace)]
self.senders = [
AuroraSender(
10 * BYTES_PER_PACKET /
(self.current_trace.get_delay(0) * 2 / 1000), self.features,
self.history_len, 0, 0, self.current_trace)
]
self.net = Network(self.senders, self.links, self.record_pkt_log)
self.run_dur = 0.01
self.steps_taken = 0
self.action_space = spaces.Box(np.array([-1e12]),
np.array([1e12]),
dtype=np.float32)
single_obs_min_vec = sender_obs.get_min_obs_vector(self.features)
single_obs_max_vec = sender_obs.get_max_obs_vector(self.features)
self.observation_space = spaces.Box(np.tile(single_obs_min_vec,
self.history_len),
np.tile(single_obs_max_vec,
self.history_len),
dtype=np.float32)
self.reward_sum = 0.0
self.reward_ewma = 0.0
self.episodes_run = -1
def __init__(
self,
traces,
history_len=10,
# features="sent latency inflation,latency ratio,send ratio",
features="sent latency inflation,latency ratio,recv ratio",
train_flag=False,
delta_scale=1.0,
config_file=None,
record_pkt_log: bool = False):
"""Network environment used in simulation.
congestion_control_type: aurora is pcc-rl. cubic is TCPCubic.
"""
self.record_pkt_log = record_pkt_log
self.config_file = config_file
self.delta_scale = delta_scale
self.traces = traces
self.difficulty_trace_cache = {0: [], 1: [], 2: [], 3: [], 4: []}
# self.baseline = BBR_old(False)
self.baseline = Cubic(False)
self.curr_diff = 0
if self.config_file is None:
self.current_trace = np.random.choice(self.traces)
else:
self.insert_to_difficulty_cache(traces)
self.current_trace = self.sample_trace(self.curr_diff)
self.train_flag = train_flag
self.use_cwnd = False
self.history_len = history_len
# print("History length: %d" % history_len)
self.features = features.split(",")
# print("Features: %s" % str(self.features))
self.links = None
self.senders = None
self.create_new_links_and_senders()
self.net = Network(self.senders, self.links, self)
self.run_dur = None
self.run_period = 0.1
self.steps_taken = 0
self.debug_thpt_changes = False
self.last_thpt = None
self.last_rate = None
if self.use_cwnd:
self.action_space = spaces.Box(np.array([-1e12, -1e12]),
np.array([1e12, 1e12]),
dtype=np.float32)
else:
self.action_space = spaces.Box(np.array([-1e12]),
np.array([1e12]),
dtype=np.float32)
self.observation_space = None
# use_only_scale_free = True
single_obs_min_vec = sender_obs.get_min_obs_vector(self.features)
single_obs_max_vec = sender_obs.get_max_obs_vector(self.features)
self.observation_space = spaces.Box(np.tile(single_obs_min_vec,
self.history_len),
np.tile(single_obs_max_vec,
self.history_len),
dtype=np.float32)
# single_obs_min_vec = np.array([0, 0, -1e12, 0, 0, 0, 0])
# single_obs_max_vec = np.array([1e12, 1e12, 1e12, 1, 1e12, 1e12, 1e12])
# self.observation_space = spaces.Box(single_obs_min_vec,
# single_obs_max_vec,
# dtype=np.float32)
self.reward_sum = 0.0
self.reward_ewma = 0.0
self.episodes_run = -1
def __init__(self, traces, history_len=10,
# features="sent latency inflation,latency ratio,send ratio",
features="sent latency inflation,latency ratio,recv ratio",
train_flag=False, delta_scale=1.0, config_file=None,
record_pkt_log: bool = False, real_trace_prob: float = 0):
"""Network environment used in simulation.
congestion_control_type: aurora is pcc-rl. cubic is TCPCubic.
"""
self.real_trace_prob = real_trace_prob
self.record_pkt_log = record_pkt_log
self.config_file = config_file
self.delta_scale = delta_scale
self.traces = traces
self.train_flag = train_flag
if self.config_file:
self.current_trace = generate_traces(self.config_file, 1, 30)[0]
elif self.traces:
self.current_trace = np.random.choice(self.traces)
else:
raise ValueError
if self.train_flag and self.traces:
self.real_trace_configs = []
for trace in self.traces:
self.real_trace_configs.append(trace.real_trace_configs(True))
self.real_trace_configs = np.array(self.real_trace_configs).reshape(-1, 4)
else:
self.real_trace_configs = None
self.use_cwnd = False
self.history_len = history_len
# print("History length: %d" % history_len)
self.features = features.split(",")
# print("Features: %s" % str(self.features))
self.links = None
self.senders = None
self.create_new_links_and_senders()
self.net = Network(self.senders, self.links, self)
self.run_dur = None
self.run_period = 0.1
self.steps_taken = 0
self.debug_thpt_changes = False
self.last_thpt = None
self.last_rate = None
if self.use_cwnd:
self.action_space = spaces.Box(
np.array([-1e12, -1e12]), np.array([1e12, 1e12]), dtype=np.float32)
else:
self.action_space = spaces.Box(
np.array([-1e12]), np.array([1e12]), dtype=np.float32)
self.observation_space = None
# use_only_scale_free = True
single_obs_min_vec = sender_obs.get_min_obs_vector(self.features)
single_obs_max_vec = sender_obs.get_max_obs_vector(self.features)
self.observation_space = spaces.Box(np.tile(single_obs_min_vec, self.history_len),
np.tile(single_obs_max_vec,
self.history_len),
dtype=np.float32)
self.reward_sum = 0.0
self.reward_ewma = 0.0
self.episodes_run = -1