def get_assignment_list(self):
from control import domains
from virtual import nodes
assignment = {}
for node in self.get_hosts(types.NODE):
for domain_name in node.domains.keys():
assignment[domains.index_of(domain_name)] = nodes.index_of(node.name)
return assignment
def start(self):
print 'Connecting with Times'
connection = times_client.connect()
self.min_ts_length = sys.maxint # Minimum length across all TS
ts_freq = 0 # Frequency of the TS from Times
# Iterate over all domains and assign them a TS
for domain in self.model.get_hosts(model.types.DOMAIN):
# Select and load TS (based on the configuration)
index = domains.index_of(domain.name)
mapping = domains.domain_profile_mapping[index]
# load = profiles.get_cpu_profile_for_initial_placement(mapping.profileId)
load = profiles.get_cpu_profile_for_initial_placement(mapping.profileId)
ts = connection.load(load)
# Convert TS to a numpy array
# select TS not time index
ts_freq = ts.frequency
ts = wutil.to_array(ts)[1]
# Add noise to the time series
if NOISE:
# random = np.random.lognormal(mean=NOISE_MEAN, sigma=NOISE_SIGMA, size=len(ts))
random = np.random.normal(loc=NOISE_MEAN, scale=NOISE_SIGMA, size=len(ts))
ts += random
ts[ts > 100] = 100
ts[ts < 0] = 0
# Attach TS to domain
domain.ts = ts
# Update max length
self.min_ts_length = min(self.min_ts_length, len(ts))
# Close times connection
times_client.close()
# Reduce length of time series to 6 hours
# Calculation: Adjust frequency by (new duration / current TS duration)
self.freq = (ts_freq * profiles.EXPERIMENT_DURATION) / (self.min_ts_length * ts_freq)
# Calculate ramp up delete time
self.ramp_up = profiles.RAMP_UP
self.ramp_down = profiles.RAMP_DOWN
# Schedule message pump
self.pump.callLater(0, self.run)