def test_read_write_tm(self):
tm = fnss.static_traffic_matrix(self.G, mean=10, stddev=0.1, max_u=0.9)
tmp_tm_file = path.join(TMP_DIR, 'tms.xml')
fnss.write_traffic_matrix(tm, tmp_tm_file)
read_tm = fnss.read_traffic_matrix(tmp_tm_file)
u, v = tm.od_pairs()[2]
self.assertAlmostEqual(tm[(u, v)], read_tm[(u, v)])
def test_read_write_tm(self):
tm = fnss.static_traffic_matrix(self.G, mean=10, stddev=0.1, max_u=0.9)
tmp_tm_file = path.join(TMP_DIR, 'tms.xml')
fnss.write_traffic_matrix(tm, tmp_tm_file)
read_tm = fnss.read_traffic_matrix(tmp_tm_file)
u, v = tm.od_pairs()[2]
self.assertAlmostEqual(tm[(u, v)], read_tm[(u, v)])
def test_read_write_tms(self):
tms = fnss.stationary_traffic_matrix(self.G, mean=10, stddev=0.1, gamma=1.2,
log_psi=-0.3, n=5, max_u=0.9)
tmp_tms_file = path.join(TMP_DIR, 'tms.xml')
fnss.write_traffic_matrix(tms, tmp_tms_file)
read_tms = fnss.read_traffic_matrix(tmp_tms_file)
u, v = tms[3].od_pairs()[2]
self.assertAlmostEqual(tms[3][(u, v)], read_tms[3][(u, v)])
def test_read_write_tms(self):
tms = fnss.stationary_traffic_matrix(self.G, mean=10, stddev=0.1, gamma=1.2,
log_psi=-0.3, n=5, max_u=0.9)
tmp_tms_file = path.join(TMP_DIR, 'tms.xml')
fnss.write_traffic_matrix(tms, tmp_tms_file)
read_tms = fnss.read_traffic_matrix(tmp_tms_file)
u, v = tms[3].od_pairs()[2]
self.assertAlmostEqual(tms[3][(u, v)], read_tms[3][(u, v)])
links=topology.edges(), # 'links' argument
)
# Now let's create a schedule with link restoration events
# We assume that the duration of a failure is exponentially distributed with
# average 1 minute.
restore_schedule = fnss.EventSchedule(t_start=0, t_unit='min')
for failure_time, event in event_schedule:
link = event['link']
restore_time = failure_time + random.expovariate(1)
restore_schedule.add(time=restore_time,
event={'link': link, 'action': 'up'},
absolute_time=True
)
# Now merge failure and restoration schedules
# After merging events are still chronologically sorted
event_schedule.add_schedule(restore_schedule)
# Note: there are several ways to create this link failure-restoration schedule
# This method has been used to illustrate a variety of functions and methods
# that FNSS provides to manipulate event schedules
# Write topology, event schedule and traffic matrix to files
fnss.write_topology(topology, 'topology.xml')
fnss.write_event_schedule(event_schedule, 'event_schedule.xml')
fnss.write_traffic_matrix(traffic_matrix, 'traffic_matrix.xml')
event_generator=rand_failure, # event gen function
links=topology.edges(), # 'links' argument
)
# Now let's create a schedule with link restoration events
# We assume that the duration of a failure is exponentially distributed with
# average 1 minute.
restore_schedule = fnss.EventSchedule(t_start=0, t_unit='min')
for failure_time, event in event_schedule:
link = event['link']
restore_time = failure_time + random.expovariate(1)
restore_schedule.add(time=restore_time,
event={
'link': link,
'action': 'up'
},
absolute_time=True)
# Now merge failure and restoration schedules
# After merging events are still chronologically sorted
event_schedule.add_schedule(restore_schedule)
# Note: there are several ways to create this link failure-restoration schedule
# This method has been used to illustrate a variety of functions and methods
# that FNSS provides to manipulate event schedules
# Write topology, event schedule and traffic matrix to files
fnss.write_topology(topology, 'topology.xml')
fnss.write_event_schedule(event_schedule, 'event_schedule.xml')
fnss.write_traffic_matrix(traffic_matrix, 'traffic_matrix.xml')
stddev=0.05, # this is the std among average flows of different OD pairs
gamma=0.8, # gamma and log_psi are parameters for fitting the std of
log_psi=-0.33, # volume fluctuations over time. Look at Nucci et al. paper
delta=0.2, # traffic variation from period max and avg as fraction of average
n=24, # number of samples per each period
periods=7, # number of periods
max_u=0.9, # max link utilization desired
origin_nodes=None, # Specify origin and destination nodes. If None,
destination_nodes=None # all nodes of the topology are both
) # origin and destination nodes of traffic
# now we generate a static traffic matrix, but this time instead of generating
# a matrix where all nodes are both origin and destinations, we pick up only
# few nodes as sources and destinations of traffic.
# Let's select 5 sources and 5 destinations
nodes = topology.nodes()
origins = random.sample(nodes, 5)
destinations = random.sample(nodes, 5)
# generate traffic matrix
tms = fnss.static_traffic_matrix(topology, mean=0.5, stddev=0.05, max_u=0.9,
origin_nodes=origins,
destination_nodes=destinations)
# save topology on a file
fnss.write_topology(topology, 'topology.xml')
# save traffic matrices on files
fnss.write_traffic_matrix(tmc, 'cyclostationary-traffic-matrix.xml')
fnss.write_traffic_matrix(tms, 'static-traffic-matrix.xml')
event_schedule = fnss.poisson_process_event_schedule(
avg_interval=0.5, # 0.5 min = 30 sec
t_start=0, # starts at 0
duration=60, # 2 hours
t_unit="min", # minutes
event_generator=rand_failure, # event gen function
links=topology.edges(), # 'links' argument
)
# Now let's create a schedule with link restoration events
# We assume that the duration of a failure is exponentially distributed with
# average 1 minute.
restore_schedule = fnss.EventSchedule(t_start=0, t_unit="min")
for failure_time, event in event_schedule:
link = event["link"]
restore_time = failure_time + random.expovariate(1)
restore_schedule.add(time=restore_time, event={"link": link, "action": "up"}, absolute_time=True)
# Now merge failure and restoration schedules
# After merging events are still chronologically sorted
event_schedule.add_schedule(restore_schedule)
# Note: there are several ways to create this link failure-restoration schedule
# This method has been used to illustrate a variety of functions and methods
# that FNSS provides to manipulate event schedules
# Write topology, event schedule and traffic matrix to files
fnss.write_topology(topology, "topology.xml")
fnss.write_event_schedule(event_schedule, "event_schedule.xml")
fnss.write_traffic_matrix(traffic_matrix, "traffic_matrix.xml")