from marl import *
from writer import writeResults, makeResultsAverage
hosts_p = 14
results = marlExperiment(
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[hosts_p, hosts_p],
explore_episodes=0.3,
episodes=10, #500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
dt=0.01,
rf="ctl",
rand_seed=0xcafed00d)
writeResults("../../results/online-14.csv", results)
makeResultsAverage("../../results/online-14.csv",
"../../results/online-14-avg.csv")
from writer import writeResults, makeResultsAverage
hosts_p = 4
results = marlExperiment(
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[hosts_p, hosts_p],
explore_episodes=0.8,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=100000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
dt=0.05,
# old_style=True,
rf="ctl",
use_controller=True,
actions_target_flows=True,
estimate_const_limit=True,
)
writeResults("../../results/soln-ext-cap-4.csv", results)
makeResultsAverage("../../results/soln-ext-cap-4.csv",
"../../results/soln-ext-cap-4-avg.csv")
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0.9,
#model = "nginx",
dt=0.05, #0.01,
# old_style=True,
rf="ctl",
use_controller=True,
#reward_direction = "out",
actions_target_flows=True,
#estimate_const_limit = True,
spiffy_mode=True,
#randomise = True,
#randomise_count = 1,
#randomise_new_ip = True,
split_codings=True,
trs_maxtime=0.001,
feature_max=18,
single_learner=True,
)
writeResults("../../results/spf-d5.csv", results)
makeResultsAverage("../../results/spf-d5.csv", "../../results/spf-d5-avg.csv")
from marl import *
from writer import writeResults, makeResultsAverage
host_p = 8
results = marlExperiment(
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[host_p, host_p],
explore_episodes=0.8,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
dt=0.05, #0.01,
# old_style=True,
rf="ctl")
writeResults("../../results/online-8-e-8.csv", results)
makeResultsAverage("../../results/online-8-e-8.csv",
"../../results/online-8-e-8-avg.csv")
from marl import *
from writer import writeResults, makeResultsAverage
results = marlExperiment(
n_teams = 5,
n_inters = 2,
n_learners = 3,
host_range = [2, 2],
explore_episodes = 0.3,
episodes = 50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length = 10000,
separate_episodes = True,
alpha = 0.05,
epsilon = 0.2,
discount = 0,
#break_equal = True,
dt = 0.01,
# old_style=True,
rf = "ctl"
)
writeResults("../../results/online-uneven.csv", results)
makeResultsAverage("../../results/online-uneven.csv", "../../results/online-avg-uneven.csv")
hosts_p = 16
results = marlExperiment(
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[hosts_p, hosts_p],
explore_episodes=0.8,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=100000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
dt=0.01,
# old_style=True,
rf="ctl",
use_controller=True,
actions_target_flows=True,
#estimate_const_limit = True,
)
writeResults("../../results/soln-ext-16.csv", results)
makeResultsAverage("../../results/soln-ext-16.csv",
"../../results/soln-ext-16-avg.csv")
from marl import *
from writer import writeResults, makeResultsAverage
results = marlExperiment(
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[2, 2],
explore_episodes=0.3,
episodes=
15, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
dt=0.05, #0.01,
# old_style=True,
rf="ctl")
writeResults("../../results/online-2.csv",
results,
times_dir="../../results/old-calc-times.csv")
makeResultsAverage("../../results/online-2.csv",
"../../results/online-2-avg.csv")
results = marlExperiment(
n_teams = 2,#5,
n_inters = 2,
n_learners = 3,
host_range = [hosts_p, hosts_p],
explore_episodes = 0.3,
episodes = 10,#50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length = 10000,
separate_episodes = True,
alpha = 0.05,
epsilon = 0.2,
discount = 0,
dt = 0.05,#0.01,
# old_style=True,
rf = "ctl",
use_controller = True,
actions_target_flows = True,
)
writeResults("../../results/soln-8.csv", results)
makeResultsAverage("../../results/soln-8.csv", "../../results/soln-8-avg.csv")
# test to handle bi-directional
evil_range=[4, 7],
explore_episodes=0.8,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
model="nginx",
dt=0.05, #0.01,
# old_style=True,
rf="ctl",
use_controller=True,
reward_direction="out",
actions_target_flows=True,
estimate_const_limit=True,
spiffy_mode=True,
randomise=True,
randomise_count=1,
randomise_new_ip=False,
split_codings=True,
)
writeResults("../../results/spf-8-ng.csv", results)
makeResultsAverage("../../results/spf-8-ng.csv",
"../../results/spf-8-avg-ng.csv")
from marl import *
from writer import writeResults, makeResultsAverage
results = marlExperiment(
P_good=1,
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[2, 2],
explore_episodes=0.3,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
model="nginx",
submodel="http",
dt=0.05, #0.01,
# old_style=True,
rf="ctl",
use_controller=True,
)
writeResults("../../results/ag-http.csv", results)
makeResultsAverage("../../results/ag-http.csv",
"../../results/ag-http-avg.csv")
from marl import *
from writer import writeResults, makeResultsAverage
results = marlExperiment(
n_teams=5,
n_inters=2,
n_learners=3,
host_range=[2, 2],
explore_episodes=0.3,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
dt=0.05, #0.01,
# old_style=True,
with_ratio=True,
rf="ctl")
writeResults("../../results/online-scale.csv", results)
makeResultsAverage("../../results/online-scale.csv",
"../../results/online-scale-avg.csv")
from marl import *
from writer import writeResults, makeResultsAverage, lastTimestepsAndEpAverages
import subprocess
import cPickle
pickle_name = "../../results/offline.pkl"
total_eps = 10000 #0
block_size = 50
# Create the file
writeResults("../../results/offline.csv", ([], [], [], [], None))
# Run these, batch into sets of 50.
for i in xrange(0, total_eps, block_size):
remaining = total_eps - i
local_block = block_size if remaining >= block_size else remaining
subprocess.call([
"python", "offline-internal.py", pickle_name,
str(local_block),
str(total_eps),
str(int(i != 0))
])
# Combine final results.
lastTimestepsAndEpAverages("../../results/offline.csv",
"../../results/offline-avg.csv")
results = marlExperiment(
n_teams = 2,#5,
n_inters = 2,
n_learners = 3,
host_range = [2, 2],
explore_episodes = 0.3,
episodes = 10,#50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length = 10000,
separate_episodes = True,
alpha = 0.05,
epsilon = 0.2,
discount = 0,
dt = 0.05,#0.01,
# old_style=True,
rf = "ctl",
override_action = 0.0,
manual_early_limit = 26.0,
)
writeResults("../../results/baseline-2.csv", results)
makeResultsAverage("../../results/baseline-2.csv", "../../results/baseline-2-avg.csv")
results = marlExperiment(
n_teams = 5,
n_inters = 2,
n_learners = 3,
host_range = [2, 2],
explore_episodes = 0.3,
episodes = 10,#50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length = 10000,
separate_episodes = True,
alpha = 0.05,
epsilon = 0.2,
discount = 0,
break_equal = True,
dt = 0.01,
# old_style=True,
protect_final_hop = False,
with_ratio = True,
rf = "ctl"
)
writeResults("../../results/online-noprot.csv", results)
makeResultsAverage("../../results/online-noprot.csv", "../../results/online-noprot-avg.csv")
from writer import writeResults, makeResultsAverage
hosts_p = 2
results = marlExperiment(
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[hosts_p, hosts_p],
explore_episodes=0.3,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
dt=0.05,
# old_style=True,
rf="ctl",
use_controller=True,
actions_target_flows=True,
estimate_const_limit=True,
)
writeResults("../../results/soln-cap-2.csv", results)
makeResultsAverage("../../results/soln-cap-2.csv",
"../../results/soln-cap-2-avg.csv")
from marl import *
from writer import writeResults, makeResultsAverage
results = marlExperiment(
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[2, 2],
explore_episodes=0.3,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
model="nginx",
submodel="udp-flood",
dt=0.05, #0.01,
# old_style=True,
rf="ctl",
use_controller=True,
)
writeResults("../../results/a-udp.csv", results)
makeResultsAverage("../../results/a-udp.csv", "../../results/a-udp-avg.csv")
params["topol"] = topol
deps.append(topols)
if model_prefix == "spiffy":
spiffy_count = int(0.1 * float(host_p * 12))
if topol == "ecmp":
spiffy_count *= 3
params["spiffy_max_experiments"] = spiffy_count
params["spiffy_min_experiments"] = spiffy_count
results = marlExperiment(**params)
(rewards, good_traffic_percents, total_loads, store_sarsas, rng, action_comps) = results
file_name_part = "tnsm-highdensitylowwidth-{}".format(host_p)
file_name = file_name_part + ".csv"
file_name_avg = file_name_part + ".avg.csv"
file_name_sarsas = file_name_part + ".pickle"
file_name_deltas = file_name_part + ".deltas.csv"
csv_dir = results_dir + file_name
avg_csv_dir = results_dir + file_name_avg
sarsas_dir = results_dir + file_name_sarsas
deltas_dir = results_dir + file_name_deltas
writeResults(csv_dir, results)
makeResultsAverage(csv_dir, avg_csv_dir)
dumbWriter(deltas_dir, action_comps)
with open(sarsas_dir, "wb") as f:
cPickle.dump(store_sarsas, f)
print "{} would write to: {}".format(experiment, csv_dir)
n_learners=3,
host_range=[2, 2],
# test to handle bi-directional
evil_range=[4, 7],
explore_episodes=0.3,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
model="nginx",
dt=0.05, #0.01,
# old_style=True,
rf="ctl",
use_controller=True,
reward_direction="out",
actions_target_flows=True,
manual_early_limit=26.0,
)
writeResults("../../results/soln-2-ng.csv",
results,
times_dir="../../results/new-calc-times.csv")
makeResultsAverage("../../results/soln-2-ng.csv",
"../../results/soln-2-avg-ng.csv")
results = marlExperiment(
n_teams=2, #5,
n_inters=2,
n_learners=3,
host_range=[hosts_p, hosts_p],
explore_episodes=0.3,
episodes=
10, #50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length=10000,
separate_episodes=True,
alpha=0.05,
epsilon=0.2,
discount=0,
model="nginx",
dt=0.05, #0.01,
# old_style=True,
rf="ctl",
use_controller=True,
reward_direction="out",
evil_range=[4, 7],
randomise=True,
randomise_count=3,
randomise_new_ip=True,
)
writeResults("../../results/online-{}-ng.csv".format(hosts_p), results)
makeResultsAverage("../../results/online-{}-ng.csv".format(hosts_p),
"../../results/online-{}-avg-ng.csv".format(hosts_p))
explore_episodes = 0.3,
episodes = 10,#50,#500, Since mininet keeps running out of files even e/ cleanup
episode_length = 10000,
separate_episodes = True,
alpha = 0.05,
epsilon = 0.2,
discount = 0,
model = "nginx",
dt = 0.05,#0.01,
# old_style=True,
rf = "ctl",
use_controller = True,
override_action = 0.0,
#manual_early_limit = 26.0,
reward_direction = "out",
randomise = True,
randomise_count = 3,
)
writeResults("../../results/baseline-2-uncap-ng.csv", results)
makeResultsAverage("../../results/baseline-2-uncap-ng.csv", "../../results/baseline-2-uncap-avg-ng.csv")
