def modify_wide_network(self, topo, mean, stddev):
"""
Modifies wide area connections according to the network mean and
standard deviation. This function will also update timing parameters
of the nodes according to the tick; it will also necessarily update
some of the meta information. Returns number of modifications.
"""
# Modifications
mods = 0
# Must supply both the mean and the stddev
if not mean or not stddev:
raise ConsoleError(
"Must supply both the wide mean and wide standard deviation!")
# Compute the tick parameter and timing params
tick_model = model = topo['meta'].get('tick_param_model',
'conservative')
T = compute_tick(mean, stddev, tick_model)
# Timing parameters for individual nodes
eto = (T, 2 * T)
hbi = T / 2
aed = T / 4
# Modify each node's timing parameters
for node in topo['nodes']:
if 'election_timeout' in node:
mods += self.update_dict_value(node, 'election_timeout', eto)
if 'heartbeat_interval' in node:
mods += self.update_dict_value(node, 'heartbeat_interval', hbi)
if 'anti_entropy_delay' in node:
mods += self.update_dict_value(node, 'anti_entropy_delay', aed)
# Modify the wide links only!
for link in topo['links']:
if link['area'] == 'wide':
mods += self.update_dict_value(link, 'latency', (mean, stddev))
# Modify the meta data
mods += self.update_meta_param(topo, 'tick_param_model', tick_model)
mods += self.update_meta_param(topo, 'wide_latency', (mean, stddev))
mods += self.update_meta_param(topo, 'anti_entropy_delay', aed)
mods += self.update_meta_param(topo, 'election_timeout', eto)
mods += self.update_meta_param(topo, 'heartbeat_interval', hbi)
mods += self.update_meta_param(topo, 'latency_mean', mean)
mods += self.update_meta_param(topo, 'latency_stddev', stddev)
mods += self.update_meta_param(topo, 'tick_metric', T)
mods += self.update_meta_param(
topo, 'variable', "{}-{}ms".format(mean - 2 * stddev,
mean + 2 * stddev))
return mods
def modify_wide_network(self, topo, mean, stddev):
"""
Modifies wide area connections according to the network mean and
standard deviation. This function will also update timing parameters
of the nodes according to the tick; it will also necessarily update
some of the meta information. Returns number of modifications.
"""
# Modifications
mods = 0
# Must supply both the mean and the stddev
if not mean or not stddev:
raise ConsoleError(
"Must supply both the wide mean and wide standard deviation!"
)
# Compute the tick parameter and timing params
tick_model = model=topo['meta'].get('tick_param_model', 'conservative')
T = compute_tick(mean, stddev, tick_model)
# Timing parameters for individual nodes
eto = (T, 2*T)
hbi = T/2
aed = T/4
# Modify each node's timing parameters
for node in topo['nodes']:
if 'election_timeout' in node:
mods += self.update_dict_value(node, 'election_timeout', eto)
if 'heartbeat_interval' in node:
mods += self.update_dict_value(node, 'heartbeat_interval', hbi)
if 'anti_entropy_delay' in node:
mods += self.update_dict_value(node, 'anti_entropy_delay', aed)
# Modify the wide links only!
for link in topo['links']:
if link['area'] == 'wide':
mods += self.update_dict_value(link, 'latency', (mean, stddev))
# Modify the meta data
mods += self.update_meta_param(topo, 'tick_param_model', tick_model)
mods += self.update_meta_param(topo, 'wide_latency', (mean, stddev))
mods += self.update_meta_param(topo, 'anti_entropy_delay', aed)
mods += self.update_meta_param(topo, 'election_timeout', eto)
mods += self.update_meta_param(topo, 'heartbeat_interval', hbi)
mods += self.update_meta_param(topo, 'latency_mean', mean)
mods += self.update_meta_param(topo, 'latency_stddev', stddev)
mods += self.update_meta_param(topo, 'tick_metric', T)
mods += self.update_meta_param(topo, 'variable', "{}-{}ms".format(
mean - 2*stddev, mean + 2*stddev)
)
return mods
def tick_param(self):
return compute_tick(*self.wide, model=self.tick_model)
MAX_NODES = 150
N_LOCATIONS = 5
LOCATIONS = [
'alpha', 'bravo', 'charlie', 'delta', 'echo', 'foxtrot', 'golf', 'hotel',
'india', 'juliet', 'kilo', 'lima', 'mike', 'november', 'oscar', 'papa',
'quebec', 'romeo', 'sierra', 'tango', 'uniform', 'victor', 'whiskey',
'xray', 'yankee', 'zulu',
]
WIDE_LATENCY_MU = 300
WIDE_LATENCY_SIGMA = 50
LOCAL_LATENCY_MU = 30
LOCAL_LATENCY_SIGMA = 5
TICK_MODEL = "bailis"
T = compute_tick(WIDE_LATENCY_MU, WIDE_LATENCY_SIGMA, TICK_MODEL)
SYSTEMS = ['eventual', 'raft']
NODE_KEYS = {
"id": None,
"label": None,
"type": "storage",
"location": None,
}
EVENTUAL_NODE_KEYS = {
"consistency": "eventual",
"anti_entropy_delay": int(round(float(T) / 4.0)),
"num_neighbors": 1,
}
def tick_param(self):
return compute_tick(*self.wide, model=self.tick_model)